confounding variable

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Statistics in a Nutshell by Sarah Boslaugh

Antoine Gombaud: Chevalier de Méré, Bayesian statistics, business climate, computer age, confounding variable, correlation coefficient, experimental subject, Florence Nightingale: pie chart, income per capita, iterative process, job satisfaction, labor-force participation, linear programming, longitudinal study, meta-analysis, p-value, pattern recognition, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, purchasing power parity, randomized controlled trial, selection bias, six sigma, sparse data, statistical model, systematic bias, The Design of Experiments, the scientific method, Thomas Bayes, Two Sigma, Vilfredo Pareto

This distinction would be missed if only crude mortality rates were considered but becomes clear when a stratified analysis removes the influence of the confounding variable (age) from the outcome (mortality). There is no absolute test for confounding, but there are ways to examine the effects of potential confounders on the relationship of interest and make a reasoned decision about whether confounding is present. The general steps to follow in assessing confounding are as follows: Calculate the crude measure of association, ignoring the confounding variable. Stratify the study population by the confounding variable, that is, divide the population into smaller subgroups based on values of the confounding variable. Calculate an adjusted measure of association.

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Confounding is sometimes described as the “third variable” problem; the relationship between two variables, say exposure and disease, is mixed up or confounded with the influence of a third variable related to both of them. More than one variable can be involved in confounding, but for the sake of simplicity, we demonstrate methods to deal with a single confounding variable. Researchers in epidemiology need to be alert to the potential for confounding in their data, particularly in observational studies when group membership is not under the control of the investigator. For instance, studies of the effects of smoking on health have to take into account the fact that smoking is a voluntary behavior (people choose to smoke or not to smoke) and people who smoke can differ in many other ways (such as alcohol consumption, diet, or level of education) from those who do not.

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Matching includes all levels of the confounders but controls enrollment in the study or assignment to groups so that the confounders will be equally distributed across the groups. Matching is commonly used in case-control studies in which controls are selected to match the cases already enrolled in the study. There are different systems for matching, but the basic concept is that categories are constructed for the confounding variables, and assignment to groups is controlled so that the distribution of the confounders is the same in each group. There are two ways to implement matching. In direct matching, individuals are matched on a one-to-one basis. In frequency matching, assignment to the groups is directed or monitored so that equal numbers of the confounders are present in each group.

Bad Science by Ben Goldacre

Asperger Syndrome, classic study, confounding variable, correlation does not imply causation, disinformation, Edward Jenner, experimental subject, food desert, hygiene hypothesis, Ignaz Semmelweis: hand washing, John Snow's cholera map, Louis Pasteur, meta-analysis, Nelson Mandela, nocebo, offshore financial centre, p-value, placebo effect, public intellectual, publication bias, Richard Feynman, risk tolerance, Ronald Reagan, selection bias, selective serotonin reuptake inhibitor (SSRI), sugar pill, systematic bias, the scientific method, urban planning

To me this is not a great surprise, and it illustrates a very simple issue in epidemiological research called ‘confounding variables’: these are things which are related both to the outcome you’re measuring (wrinkles) and to the exposure you are measuring (food), but which you haven’t thought of yet. They can confuse an apparently causal relationship, and you have to think of ways to exclude or minimise confounding variables to get to the right answer, or at least be very wary that they are there. In the case of this study, there are almost too many confounding variables to describe. I eat well—with lots of olive oil, as it happens—and I don’t have many wrinkles.

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Now, to be fair to nutritionists, they are not alone in failing to understand the importance of confounding variables, in their eagerness for a clear story. Every time you read in a newspaper that ‘moderate alcohol intake’ is associated with some improved health outcome—less heart disease, less obesity, anything—to gales of delight from the alcohol industry, and of course from your friends, who say, ‘Ooh well, you see, it’s better for me to drink a little…’ as they drink a lot—you are almost certainly witnessing a journalist of limited intellect, overinterpreting a study with huge confounding variables. This is because, let’s be honest here: teetotallers are abnormal.

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There is a practical problem with this kind of research, of course, which I would hope you might spot: most people do get the MMR vaccine, so the individuals you’re measuring who didn’t get the vaccine might be unusual in other ways—perhaps their parents have refused the vaccine for ideological or cultural reasons, or the child has a pre-existing physical health problem—and those factors might themselves be related to autism. There’s little you can do in terms of study design about this potential ‘confounding variable’, because as we said, you’re not likely to do a randomised controlled trial in which you randomly don’t give children vaccines: you just throw the result into the pot with the rest of the information, in order to reach your verdict. As it happens, Smeeth et al. went to great lengths to make sure their controls were representative.

I Think You'll Find It's a Bit More Complicated Than That by Ben Goldacre

Aaron Swartz, call centre, conceptual framework, confounding variable, correlation does not imply causation, crowdsourcing, death of newspapers, Desert Island Discs, Dr. Strangelove, drug harm reduction, en.wikipedia.org, experimental subject, Firefox, Flynn Effect, Helicobacter pylori, jimmy wales, John Snow's cholera map, Loebner Prize, meta-analysis, moral panic, nocebo, placebo effect, publication bias, selection bias, selective serotonin reuptake inhibitor (SSRI), seminal paper, Simon Singh, social distancing, statistical model, stem cell, Stephen Fry, sugar pill, the scientific method, Turing test, two and twenty, WikiLeaks

Here we see how clever things called funnel plots can help to show whether one area’s healthcare really is any worse than another’s, whether an increase in antidepressant prescriptions really does mean more people are depressed (or even whether more people are taking antidepressants), and the core skill of all epidemiology: how to correct for ‘confounding variables’, or rather: how to make sure that apparent correlations in your data are real. In an overview of bicycle helmet research, we review every epidemiological error in the textbooks, and a grand claim about the benefits of screening for diseases helps show that doing something – even something small – can often be worse than doing nothing at all.

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These studies, however, are vulnerable to many methodological shortcomings. If the controls are cyclists presenting with other injuries in the emergency department, then analyses are conditional on having an accident and therefore assume that wearing a helmet does not change the overall accident risk. There are also confounding variables that are generally unmeasured and perhaps even unmeasurable. People who choose to wear bicycle helmets will probably be different from those who ride without a helmet: they may be more cautious, for example, and so less likely to have a serious head injury, regardless of their helmets. People who are forced by legislation to wear a bicycle helmet, meanwhile, may be different again.

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q=coffee+hallucinations+location%3Auk exactly what the researchers did: http://dx.doi.org/10.1016/j.paid.2008.10.032 survey is still online: http://psychology.dur.ac.uk:82/srj/caffeine2.html ‘Launay-Slade Hallucination Scale’: http://www.google.co.uk/search?q=Launay-Slade+Hallucination+Scale alternative explanations: http://en.wikipedia.org/wiki/Confounding_variable the academic paper: http://dx.doi.org/10.1016/j.paid.2008.10.032 the press release: http://www.alphagalileo.org/index.cfm?fuseaction=readrelease&releaseid=535120&ez_search=1 ‘multiple comparisons’: http://en.wikipedia.org/wiki/Multiple_comparisons no one was there: http://www.thinkgeek.com/caffeine/accessories/5a65/ draw a target around them: http://en.wikipedia.org/wiki/Texas_sharpshooter_fallacy Voices of the Ancients Voices of the Ancients: http://www.badscience.net/2010/01/voices-of-the-ancients/ Daily Mail: http://www.dailymail.co.uk/sciencetech/article-1240746/Prehistoric-sat-nav-set-ancestors-Britain.html the Metro: http://www.metro.co.uk/news/807855-did-prehistoric-satnav-help-britons-find-their-way Matt Parker: http://www.standupmaths.com/ applied the same techniques: http://bengoldacre.posterous.com/did-aliens-play-a-role-in-woolworths BIG DATA There’s Something Magical About Watching Patterns Emerge from Data There’s Something Magical: http://www.badscience.net/2011/06/theres-something-magical-about-watching-patterns-emerge-from-data/ British Medical Journal: http://www.bmj.com/content/342/bmj.d2983.full first NHS reforms: http://www.guardian.co.uk/society/nhs Give Us the Data A consultation is under way: http://c561635.r35.cf2.rackcdn.com/A-Consultation-on-Data-Policy-for-a-Public-Data-Corporation.pdf foolishly restrictive: http://pdcconsult.ernestmarples.com/ everyday government data: http://www.theguardian.com/politics/government-data forbidden to repurpose it: http://hadleybeeman.net/2011/01/26/uses-for-open-data/ TheyWorkForYou.com: http://www.theyworkforyou.com/ all our postcode information: http://en.wikipedia.org/wiki/Postcodes_in_the_United_Kingdom the house-number boundaries: http://ernestmarples.com/blog/2010/01/postcode-petition-response-our-reply/ make the government: http://pdcconsult.ernestmarples.com/ Care.data Can Save Lives: But Not If We Bungle It greatest need in the NHS http://www.theguardian.com/society/nhs at risk by the bungled: http://www.nature.com/news/power-to-the-people-1.14505?

The Book of Why: The New Science of Cause and Effect by Judea Pearl, Dana Mackenzie

affirmative action, Albert Einstein, AlphaGo, Asilomar, Bayesian statistics, computer age, computer vision, Computing Machinery and Intelligence, confounding variable, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, driverless car, Edmond Halley, Elon Musk, en.wikipedia.org, experimental subject, Great Leap Forward, Gregor Mendel, Isaac Newton, iterative process, John Snow's cholera map, Loebner Prize, loose coupling, Louis Pasteur, Menlo Park, Monty Hall problem, pattern recognition, Paul Erdős, personalized medicine, Pierre-Simon Laplace, placebo effect, Plato's cave, prisoner's dilemma, probability theory / Blaise Pascal / Pierre de Fermat, randomized controlled trial, Recombinant DNA, selection bias, self-driving car, seminal paper, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steve Jobs, strong AI, The Design of Experiments, the scientific method, Thomas Bayes, Turing test

For example, if we are testing a drug and give it to patients who are younger on average than the people in the control group, then age becomes a confounder—a lurking third variable. If we don’t have any data on the ages, we will not be able to disentangle the true effect from the spurious effect. However, the converse is also true. If we do have measurements of the third variable, then it is very easy to deconfound the true and spurious effects. For instance, if the confounding variable Z is age, we compare the treatment and control groups in every age group separately. We can then take an average of the effects, weighting each age group according to its percentage in the target population. This method of compensation is familiar to all statisticians; it is called “adjusting for Z” or “controlling for Z.”

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Note that Game 5 is embedded in this model in the sense that the variables A, B, C, X, and Y have exactly the same relationships. So we can transfer our conclusions over and conclude that we have to control for A and B or for C; but C is an unobservable and therefore uncontrollable variable. In addition we have four new confounding variables: D = parental asthma, E = chronic bronchitis, F = sex, and G = socioeconomic status. The reader might enjoy figuring out that we must control for E, F, and G, but there is no need to control for D. So a sufficient set of variables for deconfounding is A, B, E, F, and G. FIGURE 4.7. Andrew Forbes’s model of smoking (X) and asthma (Y).

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Hypothetical causal diagram for smoking and cancer, suitable for front-door adjustment. Suppose we are doing an observational study and have collected data on Smoking, Tar, and Cancer for each of the participants. Unfortunately, we cannot collect data on the Smoking Gene because we do not know whether such a gene exists. Lacking data on the confounding variable, we cannot block the back-door path Smoking Smoking Gene Cancer. Thus we cannot use back-door adjustment to control for the effect of the confounder. So we must look for another way. Instead of going in the back door, we can go in the front door! In this case, the front door is the direct causal path Smoking Tar Cancer, for which we do have data on all three variables.

Mindware: Tools for Smart Thinking by Richard E. Nisbett

affirmative action, Albert Einstein, availability heuristic, behavioural economics, big-box store, Cass Sunstein, choice architecture, cognitive dissonance, confounding variable, correlation coefficient, correlation does not imply causation, cosmological constant, Daniel Kahneman / Amos Tversky, dark matter, do well by doing good, Edward Jenner, endowment effect, experimental subject, feminist movement, fixed income, fundamental attribution error, Garrett Hardin, glass ceiling, Henri Poincaré, if you see hoof prints, think horses—not zebras, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, job satisfaction, Kickstarter, lake wobegon effect, libertarian paternalism, longitudinal study, loss aversion, low skilled workers, Menlo Park, meta-analysis, Neil Armstrong, quantitative easing, Richard Thaler, Ronald Reagan, selection bias, Shai Danziger, Socratic dialogue, Steve Jobs, Steven Levy, tacit knowledge, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, William of Occam, Yitang Zhang, Zipcar

Occasional acid indigestion but don’t know exactly why? Keep a log of food and drink every day with special attention to likely culprits such as alcohol, coffee, soda, and chocolate. Then conduct an actual randomized experiment—flip a coin to decide whether to have a cocktail. And vary one thing at a time to avoid confounding variables. If you stop eating chocolate and drinking soda and your reflux improves, you won’t know whether it’s the food or the beverage that’s the guilty party. Chapter 12 on verbal report, after considering some more scientific methodology, offers lots more suggestions about experimenting on yourself.

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We’re almost never able to make that claim. We can only measure what we assume might be important and leave out the infinity of variables that we don’t assume are important. But ATTBW: Assumptions Tend to Be Wrong. So the battle is usually lost right there. Second, how well do we measure each of the possible confounding variables? If we measure a variable poorly, we haven’t controlled for it enough. If we measure a variable so poorly that it has no validity, we haven’t controlled for anything. Sometimes MRA is the only research tool available for examining interesting and important questions. An example is the question of whether religious belief and practice are associated with greater or lesser rates of procreation.

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Does the Buddhist practice of “loving-kindness”—visualizing smiling at others, reflecting on their positive qualities and their acts of generosity, and repeating the words “loving-kindness”—bring you peace and relieve you of anger toward others? A problem with experiments on the self is that you’re dealing with an N of 1. An advantage, however, is that experiments on the self automatically have a within, before/after design, which can improve accuracy because of the reduction in error variance. You can also keep confounding variables to a minimum. If you’re looking to discover the effect of some factor on you, try to keep everything else constant across the study period when you’re comparing presence of the factor versus absence of the factor. That way you can have a fairly good experiment. Don’t take up yoga at the same time as you move from one house to another or break up with your boyfriend.

How Medicine Works and When It Doesn't: Learning Who to Trust to Get and Stay Healthy by F. Perry Wilson

Affordable Care Act / Obamacare, barriers to entry, Barry Marshall: ulcers, cognitive bias, Comet Ping Pong, confounding variable, coronavirus, correlation does not imply causation, COVID-19, data science, Donald Trump, fake news, Helicobacter pylori, Ignaz Semmelweis: hand washing, Louis Pasteur, medical malpractice, meta-analysis, multilevel marketing, opioid epidemic / opioid crisis, p-value, personalized medicine, profit motive, randomized controlled trial, risk tolerance, selection bias, statistical model, stem cell, sugar pill, the scientific method, Thomas Bayes

Ice cream sales are correlated with the murder rate because both things happen more in the summer (ice cream sales because the temperature is hot and ice cream is cold and delicious, murders because more people are outside, leading to more confrontations). We say that outdoor temperature confounds the observed association between ice cream sales and murder rates. A confounding variable is one that is linked to the exposure of interest and the outcome of interest, and thus induces the illusion of causation between the exposure and the outcome. Another example: In 1999, an article appeared in Nature (one of the most prestigious scientific publications) which found that children who slept with a light on were much more likely to be nearsighted when they grew up.

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Another example: In 1999, an article appeared in Nature (one of the most prestigious scientific publications) which found that children who slept with a light on were much more likely to be nearsighted when they grew up. The press latched on to this with a causal explanation that perhaps the light exposure at night was limiting eye growth in a way that would promote poor vision. In fact, there was no causal relationship between leaving the light on and poor vision. Future studies found that there was a confounding variable—parental nearsightedness—that wasn’t accounted for. It turns out that parents who are nearsighted are more likely to have kids who are nearsighted. Parents who are nearsighted are also more likely to leave the lights on at night—the easier to check on the kids. In other words, there was a missing variable in the Nature analysis.

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Second, we have a cheap, widely available, effective, and well-tolerated medicine to increase vitamin D levels; we can take supplemental vitamin D—you don’t even need a prescription. But why are those correlations so strong in the first place? In the case of vitamin D levels, we are (once again, and as usual) in the realm of confounding variables. I have often referred to vitamin D levels as the “lifestyle” biomarker. Let’s think of some behaviors that raise your vitamin D level: getting outside, eating a diet rich in fish (and some mushrooms), and exercise (particularly if you do the exercise out in the sun). In other words, your vitamin D level may merely be a marker for a bunch of healthful behaviors you engage in.

How to Read a Paper: The Basics of Evidence-Based Medicine by Trisha Greenhalgh

call centre, complexity theory, conceptual framework, confounding variable, correlation coefficient, correlation does not imply causation, deskilling, knowledge worker, longitudinal study, meta-analysis, microbiome, New Journalism, p-value, personalized medicine, placebo effect, publication bias, randomized controlled trial, selection bias, systematic bias, systems thinking, the scientific method

Table 3.1 Terms used to describe design features of clinical research studies Term Meaning Parallel group comparison Each group receives a different treatment, with both groups being entered at the same time. In this case, results are analysed by comparing groups. Paired (or matched) comparison Participants receiving different treatments are matched to balance potential confounding variables such as age and sex. Results are analysed in terms of differences between participant pairs. Within-participant comparison Participants are assessed before and after an intervention and results analysed in terms of within-participant changes. Single-blind Participants did not know which treatment they were receiving.

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The details of how these different features of teetotalism were controlled for by the epidemiologists are discussed elsewhere [8] [9]. Interestingly, when I was writing the third edition of this book in 2005, the conclusion at that time was that even when due allowance was made in the analysis for potential confounding variables in people who described themselves as non-drinkers, these individuals' increased risk of premature mortality remained (i.e. the J curve was a genuine phenomenon) [8]. But by the time I wrote the fourth edition in 2010, a more sophisticated analysis of the various cohort studies (i.e. which controlled more carefully for ‘sick quitters’) had been published [9].

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A change in a numerical value may be clinically significant without being statistically significant or vice versa (see section ‘Probability and confidence’), and may also be vulnerable to various biases. For example, in a before and after study, time will have moved on between the ‘baseline’ and ‘post intervention’ measures, and a host of confounding variables including the economic climate, public attitudes, availability of particular drugs or procedures, relevant case law, and the identity of the chief executive, may have changed. Qualitative outcomes may be particularly vulnerable to the Hawthorne effect (staff tend to feel valued and work harder when any change in working conditions aimed at improving performance is introduced, whether it has any intrinsic merits or not) [16].

Back to School: Why Everyone Deserves a Second Chance at Education by Mike Rose

blue-collar work, centre right, confounding variable, creative destruction, delayed gratification, digital divide, George Santayana, income inequality, MITM: man-in-the-middle, moral panic, new economy, Ronald Reagan, The Bell Curve by Richard Herrnstein and Charles Murray, the built environment, urban renewal, War on Poverty

In writing, fundamentals would be the rules of grammar and punctuation as represented in those workbook exercises. In addition to breaking down, you want to keep a tight focus on the task—writing—and remove potentially confounding variables, like reading skill. So if readings are used, they are usually kept simple and at a minimum. This parsing out of reading from writing is structurally reinforced in many institutions with reading and writing each having its own department. Another potentially 121 BAC K TO S C HO OL confounding variable you want to control for is complexity of topic: what students write about if writing beyond the sentence is involved. The standard remedial playbook for decades and decades includes topics involving one’s personal experience (“Write about an event that changed your life”) or a broad social issue (“Why should we vote?”).

Our Kids: The American Dream in Crisis by Robert D. Putnam

assortative mating, business cycle, classic study, confounding variable, correlation does not imply causation, deindustrialization, demographic transition, desegregation, digital divide, ending welfare as we know it, epigenetics, full employment, George Akerlof, helicopter parent, impulse control, income inequality, index card, jobless men, longitudinal study, low skilled workers, machine readable, manufacturing employment, mass incarceration, meta-analysis, mortgage tax deduction, new economy, Occupy movement, Ralph Waldo Emerson, randomized controlled trial, school choice, selection bias, Socratic dialogue, The Bell Curve by Richard Herrnstein and Charles Murray, the built environment, the strength of weak ties, upwardly mobile, Walter Mischel, white flight, working poor

They had time and money that the poorer kids’ families lacked, and they invested those resources in helping their children acquire valuable soft skills through extracurricular activities. Consistent involvement in extracurricular activities is strongly associated with a variety of positive outcomes during the school years and beyond—even after controlling for family background, cognitive skills, and many other potentially confounding variables. These positive outcomes include higher grade-point averages, lower dropout rates, lower truancy, better work habits, higher educational aspirations, lower delinquency rates, greater self-esteem, more psychological resilience, less risky behavior, more civic engagement (like voting and volunteering), and higher future wages and occupational attainment.50 One carefully controlled study, for example, showed that kids consistently involved in extracurricular activities were 70 percent more likely to go to college than kids who were only episodically involved—and roughly 400 percent more likely than kids who were not at all involved.51 Another study, which has a special relevance to the students we met in Orange County, found that involvement in extracurricular activities among low-income Latino students (all too rare, as the experiences of Lola and Sofia illustrate) predicts school achievement.52 Leadership in extracurricular activities appears to have even more intense effects: one study found that club and team leaders are more likely to command higher salaries in managerial positions later in life.53 And an intriguing study of students who attended high school in Cleveland, Ohio, in the 1940s even found neurological effects a half century later: students who had participated in extracurricular activities were substantially less likely than those who hadn’t to suffer from dementia at the turn of the century, even after adjusting for differences in IQ and educational attainment.54 The only negative finding that emerges from the dozens of studies that have been done on the correlates of extracurricular activities is not startling: among young men, participation in sports is often correlated with excessive drinking (but not drug use).

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Careful, independent evaluations have shown that formal mentoring can help at-risk kids to develop healthy relations with adults (including parents), and in turn to achieve significant gains in academic and psychosocial outcomes—school attendance, school performance, self-worth, and reduced substance abuse, for example—even with careful controls for potentially confounding variables. These measurable effects are strongest when the mentoring relationship is long-term, and strongest for at-risk kids. (Upper-class kids already have informal mentors in their lives, so adding a formal mentor does not add so much to their achievement.) Measurably, mentoring matters.23 Formal mentoring is much less common and less enduring than informal mentoring.

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Based on unpublished analyses by Carl Frederick of 2011–2012 data on school quality measures for 85 percent of all public K–8 and high schools in the country, as compiled and published in 2014 by the Office of Civil Rights of the U.S. Department of Education, available at http://ocrdata.ed.gov/. With controls for other potentially confounding variables, including the racial composition of the high school, the fraction of the student body eligible for free or reduced-price lunches, a widely used proxy for student poverty, is uncorrelated with the ratio of counselors to students and is positively correlated with more teachers per 100 students.

Data Science from Scratch: First Principles with Python by Joel Grus

backpropagation, confounding variable, correlation does not imply causation, data science, deep learning, Hacker News, higher-order functions, natural language processing, Netflix Prize, p-value, Paul Graham, recommendation engine, SpamAssassin, statistical model

Correlation after removing the outlier You investigate further and discover that the outlier was actually an internal test account that no one ever bothered to remove. So you feel pretty justified in excluding it. Simpson’s Paradox One not uncommon surprise when analyzing data is Simpson’s Paradox, in which correlations can be misleading when confounding variables are ignored. For example, imagine that you can identify all of your members as either East Coast data scientists or West Coast data scientists. You decide to examine which coast’s data scientists are friendlier: coast # of members avg. # of friends West Coast 101 8.2 East Coast 103 6.5 It certainly looks like the West Coast data scientists are friendlier than the East Coast data scientists.

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closeness centrality, Betweenness Centrality clustering, Clustering-For Further Explorationbottom-up hierarchical clustering, Bottom-up Hierarchical Clustering-Bottom-up Hierarchical Clustering choosing k, Choosing k example, clustering colors, Example: Clustering Colors example, meetups, Example: Meetups-Example: Meetups k-means clustering, The Model clusters, Rescaling, The Ideadistance between, Bottom-up Hierarchical Clustering code examples from this book, Using Code Examples coefficient of determination, The Model combiners (in MapReduce), An Aside: Combiners comma-separated values files, Delimited Filescleaning comma-delimited stock prices, Cleaning and Munging command line, running Python scripts at, stdin and stdout conditional probability, Conditional Probabilityrandom variables and, Random Variables confidence intervals, Confidence Intervals confounding variables, Simpson’s Paradox confusion matrix, Correctness continue statement (Python), Control Flow continuity correction, Example: Flipping a Coin continuous distributions, Continuous Distributions control flow (in Python), Control Flow correctness, Correctness correlation, Correlationand causation, Correlation and Causation in simple linear regression, The Model other caveats, Some Other Correlational Caveats outliers and, Correlation Simpson's Paradox and, Simpson’s Paradox correlation function, Simple Linear Regression cosine similarity, User-Based Collaborative Filtering, Item-Based Collaborative Filtering Counter (Python), Counter covariance, Correlation CREATE TABLE statement (SQL), CREATE TABLE and INSERT cumulative distribution function (cdf), Continuous Distributions currying (Python), Functional Tools curse of dimensionality, The Curse of Dimensionality-The Curse of Dimensionality, User-Based Collaborative Filtering D D3.js library, Visualization datacleaning and munging, Cleaning and Munging exploring, Exploring Your Data-Many Dimensions finding, Find Data getting, Getting Data-For Further Explorationreading files, Reading Files-Delimited Files scraping from web pages, Scraping the Web-Example: O’Reilly Books About Data using APIs, Using APIs-Using Twython using stdin and stdout, stdin and stdout manipulating, Manipulating Data-Manipulating Data rescaling, Rescaling-Rescaling data mining, What Is Machine Learning?

The Great Stagnation by Tyler Cowen

Asian financial crisis, Bernie Madoff, Black Monday: stock market crash in 1987, confounding variable, en.wikipedia.org, endogenous growth, financial innovation, Flynn Effect, income inequality, indoor plumbing, life extension, liquidity trap, Long Term Capital Management, Mark Zuckerberg, meta-analysis, Peter Thiel, RAND corporation, Savings and loan crisis, school choice, scientific management, Tyler Cowen, Tyler Cowen: Great Stagnation, urban renewal

We don’t know. The scholarly literature on K-12 education suggests there is no obvious “eyeball-ready” correlation between how much money is spent in U.S. public schools and the quality of final outcomes. On the other hand, you can find studies that parse the data more closely and try to adjust for confounding variables, to claim real returns from higher educational spending. One way of reconciling these contrasting results is to believe that money yields better outcomes when well spent. But how often is that the case? If we are asking the fundamental question of how wealthy we are, it is the absolute rather than the statistically adjusted education results that matter, and we are again back to mediocre performance.

Are We Getting Smarter?: Rising IQ in the Twenty-First Century by James R. Flynn

confounding variable, Flynn Effect, longitudinal study, meta-analysis, out of africa, popular electronics, traumatic brain injury, twin studies

The laws can be described as follows: (1) a mistaken deinition of intelligence; (2) ignoring that all human behavior requires at least three levels of explanation; (3) ignoring the signiicance of comparative measurements; and (4) ignoring the fact that social science methodology can eliminate the possibility of confounding variables without reference to brain physiology. Jensen deines intelligence in terms of events in the brain and nervous system. This is no more sensible than deining extroversion in terms of physiological events. There may be a physiological description that explains who is extroverted. But the only reason we are aware of that is because it correlates with extroversion deined as being outgoing in your interaction with other people.

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We have no absolute measure of the war-making behavior of the Allies and Axis powers during World War II, and certainly cannot reduce their behavior to the physiological level, but we know who won. I cannot give an absolute measure of the ability to classify or use logic on the hypothetical, but I can say we are much better at both today than our ancestors were in 1900. The possibility of confounding variables afflicts all levels of explanation, and science can often deal with them level by level. Do larger brains signal that intelligence has increased or that people have just got bigger? The irst step is to calculate a brain-size-to-body-mass ratio and see if that correlates with IQ. Is it possible that more exposure to tests causes IQ gains over time?

The Art of Statistics: Learning From Data by David Spiegelhalter

Abraham Wald, algorithmic bias, Anthropocene, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Brexit referendum, Carmen Reinhart, Charles Babbage, complexity theory, computer vision, confounding variable, correlation coefficient, correlation does not imply causation, dark matter, data science, deep learning, DeepMind, Edmond Halley, Estimating the Reproducibility of Psychological Science, government statistician, Gregor Mendel, Hans Rosling, Higgs boson, Kenneth Rogoff, meta-analysis, Nate Silver, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, randomized controlled trial, recommendation engine, replication crisis, self-driving car, seminal paper, sparse data, speech recognition, statistical model, sugar pill, systematic bias, TED Talk, The Design of Experiments, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Two Sigma

A regression analysis had the rate of tumours as the dependent, or response, variable, and education as the independent, or explanatory, variable of interest. Other factors entered into the regression included age at diagnosis, calendar year, region of Sweden, marital status and income, all of which were considered to be potential confounding variables. This adjustment for confounders is an attempt to tease out a purer relationship between education and brain tumours, but it can never be wholly adequate. There will always remain the suspicion that some other lurking process might be at work, such as those with higher education seeking better health care and increased diagnoses.

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signal and the noise: the idea that observed data arises from two components: a deterministic signal which we are really interested in, and random noise that comprises the residual error. The challenge of statistical inference is to appropriately identify the two, and not be misled into thinking that noise is actually a signal. Simpson’s paradox: when an apparent relationship reverses its sign when a confounding variable is taken into account. size of a test: the Type I error rate of a statistical test, generally denoted by α. skewed distribution: when a sample or population distribution is highly asymmetric, and has a long left- or right-hand tail. This might typically occur for variables such as income and sales of books, when there is extreme inequality.

Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life by Rory Sutherland

"World Economic Forum" Davos, 3D printing, Alfred Russel Wallace, barriers to entry, basic income, behavioural economics, Black Swan, Brexit referendum, butterfly effect, California gold rush, call centre, Captain Sullenberger Hudson, Cass Sunstein, cognitive dissonance, confounding variable, Daniel Kahneman / Amos Tversky, Dava Sobel, delayed gratification, Donald Trump, double helix, Downton Abbey, driverless car, Easter island, Edward Jenner, Elon Musk, Firefox, Ford Model T, General Magic , George Akerlof, gig economy, Google Chrome, Google X / Alphabet X, Grace Hopper, Hyperloop, Ignaz Semmelweis: hand washing, IKEA effect, information asymmetry, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Dyson, John Harrison: Longitude, loss aversion, low cost airline, Mason jar, Murray Gell-Mann, nudge theory, Peter Thiel, placebo effect, race to the bottom, Richard Feynman, Richard Thaler, Rory Sutherland, shareholder value, Silicon Valley, social intelligence, Steve Jobs, supply-chain management, systems thinking, TED Talk, the map is not the territory, The Market for Lemons, The Wealth of Nations by Adam Smith, ultimatum game, universal basic income, Upton Sinclair, US Airways Flight 1549, Veblen good, work culture

.* To use the analogy of the needle in the haystack, more data does increase the number of needles, but it also increases the volume of hay, as well as the frequency of false needles – things we will believe are significant when really they aren’t. The risk of spurious correlations, ephemeral correlations, confounding variables or confirmation bias can lead to more dumb decisions than insightful ones, with the data giving us a confidence in these decisions that is simply not warranted. A large tech company recently developed an AI system to sift applications for jobs, but it rapidly developed extreme gender prejudices – marking people down if their CV mentioned, say, participation in women’s basketball.

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While I can see that replacing a browser on a laptop may be indicative of certain qualities – conscientiousness, technological competence and the willingness to defer gratification, to name just three – is it acceptable to use this information to discriminate between employees? The company decided that it wasn’t, in part because it would have been unfair to less privileged applicants, who may have had to use a library computer to apply. Illustration by Greg Stevenson The confounding variable here, missing from the data, is the weather, which explains the spurious correlation. To a dumb alogorithm, it might appear from the graph that ice cream consumption drove people to commit crimes. However, the real reason is simple: people consume more ice cream when it is sunnier, and they also commit more crimes on warm evenings.

The Art of Statistics: How to Learn From Data by David Spiegelhalter

Abraham Wald, algorithmic bias, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Brexit referendum, Carmen Reinhart, Charles Babbage, complexity theory, computer vision, confounding variable, correlation coefficient, correlation does not imply causation, dark matter, data science, deep learning, DeepMind, Edmond Halley, Estimating the Reproducibility of Psychological Science, government statistician, Gregor Mendel, Hans Rosling, Higgs boson, Kenneth Rogoff, meta-analysis, Nate Silver, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, randomized controlled trial, recommendation engine, replication crisis, self-driving car, seminal paper, sparse data, speech recognition, statistical model, sugar pill, systematic bias, TED Talk, The Design of Experiments, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Two Sigma

A regression analysis had the rate of tumours as the dependent, or response, variable, and education as the independent, or explanatory, variable of interest. Other factors entered into the regression included age at diagnosis, calendar year, region of Sweden, marital status and income, all of which were considered to be potential confounding variables. This adjustment for confounders is an attempt to tease out a purer relationship between education and brain tumours, but it can never be wholly adequate. There will always remain the suspicion that some other lurking process might be at work, such as those with higher education seeking better health care and increased diagnoses.

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signal and the noise: the idea that observed data arises from two components: a deterministic signal which we are really interested in, and random noise that comprises the residual error. The challenge of statistical inference is to appropriately identify the two, and not be misled into thinking that noise is actually a signal. Simpson’s paradox: when an apparent relationship reverses its sign when a confounding variable is taken into account. size of a test: the Type I error rate of a statistical test, generally denoted by α. skewed distribution: when a sample or population distribution is highly asymmetric, and has a long left- or right-hand tail. This might typically occur for variables such as income and sales of books, when there is extreme inequality.

The World of Caffeine: The Science and Culture of the World's Most Popular Drug by Bennett Alan Weinberg, Bonnie K. Bealer

British Empire, clean water, confounding variable, easy for humans, difficult for computers, Edmond Halley, Edward Lloyd's coffeehouse, gentrification, Haight Ashbury, Honoré de Balzac, Isaac Newton, Johann Wolfgang von Goethe, Lao Tzu, placebo effect, Plato's cave, spice trade, trade route, traveling salesman

Yet another confounding exposure may arise from neglect of non-dietary sources of caffeine, such as over-the-counter and prescription medicines that people may not realize contain caffeinated and so fail to report. Confounding Variables We have already noted ways in which hidden variables can baffle attempts to understand the relationship between the use of caffeine and any given health outcome. Epidemiologists call such variables “confounders” that, according to one researcher, “plague the literature” about the link between caffeine and problems in human reproduction. An example is the confounding variable of maternal age. Coffee consumption tends to increase with age throughout the childbearing years and, at the same time, the risk of many reproductive hazards also increases with age past 25 or 30.7 People who drink coffee differ in significant ways—over and beyond their use of coffee—from those who do not, and those who drink a great deal of coffee differ from those who drink less.

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Unfortunately, in the area of human health, the complexity of the human body and mind and the inability of investigators to conduct potentially dangerous experiments on human beings as part of their research often make it difficult to make reliable judgments. There are three potential weaknesses of medical studies that pose problems for those seeking to understand caffeine’s health effects: biased sample selection, inaccurately measured exposure, and failure to exclude confounding variables. Because these limitations can be seen most clearly in studies of caffeine’s effects on the outcomes of pregnancy, it is valuable to examine in detail some of the methodological problems that bedevil scientists working on these questions. While reading this section, however, the reader should keep in mind that similar or identical problems attend investigations of every area of caffeine and human health discussed in this book.1 Sample Selection Studies of the effects of caffeine consumption on reproductive hazards, including the risk of delayed conception, spontaneous abortion, prematurity, low birthweight, and major congenital malformations, multiplied like rabbits throughout the 1980s and 1990s.

Free Money for All: A Basic Income Guarantee Solution for the Twenty-First Century by Mark Walker

3D printing, 8-hour work day, additive manufacturing, Affordable Care Act / Obamacare, basic income, Baxter: Rethink Robotics, behavioural economics, Capital in the Twenty-First Century by Thomas Piketty, commoditize, confounding variable, driverless car, financial independence, full employment, guns versus butter model, happiness index / gross national happiness, industrial robot, intangible asset, invisible hand, Jeff Bezos, job automation, job satisfaction, John Markoff, Kevin Kelly, laissez-faire capitalism, late capitalism, longitudinal study, market clearing, means of production, military-industrial complex, new economy, obamacare, off grid, off-the-grid, plutocrats, precariat, printed gun, profit motive, Ray Kurzweil, rent control, RFID, Rodney Brooks, Rosa Parks, science of happiness, Silicon Valley, surplus humans, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, universal basic income, warehouse robotics, working poor

This bourgeoning segment of the labor market has been dubbed the “precariat” by Guy Standing.20 The enormous uncertainty in the lives of the precariat worker is no doubt a source of unhappiness. Even a modest BIG of $10,000 could boost happiness more than we would predict on the basis of income alone, if the fact that it is guaranteed makes a difference to how vulnerable workers feel. Universal health insurance is also another confounding variable. We might expect that some of the unhappiness of the lowest income group is due to lack of affordable health care. If BIG and universal health care were implemented at the same time, it would be 130 FREE MONEY FOR ALL hard to predict the level of happiness for the least well-off. Still, there is every reason to predict that the least well-off will gain significantly in terms of happiness.

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To illustrate, consider a study by Ed Diener and his colleagues.32 The study assessed the cheerfulness of college freshman and their income 19 years later. The group assessed as more cheerful in college earned more than their less cheerful cohorts 19 years later. The evidence here is suggestive that happiness causes increased earnings. As with any attribution of causality, there are significant worries about confounding variables. In this case, an obvious one is parental income. It does not seem out of the realm of possibility that freshmen whose parents earn more may be happier, and higher parental income may explain why their children are able to earn more. To sort out possible confounding influences, researchers “control” for such variables.

Thinking with Data by Max Shron

business intelligence, Carmen Reinhart, confounding variable, correlation does not imply causation, data science, Growth in a Time of Debt, iterative process, Kenneth Rogoff, randomized controlled trial, Richard Feynman, statistical model, The Design of Experiments, the scientific method

Natural Experiments Our best hope in setting up observational designs is to try to find natural experiments. Consider an effort to determine how being convicted of a crime in high school affects earnings from age 25 to 40. It isn’t enough to just compare earning differences between those who were convicted and those who weren’t, because clearly there will be strong confounding variables. A clever strategy would be to compare earnings between those who were arrested but not convicted of a crime, and those who were convicted. Though there are obvious differences in the groups, they are likely to be similar on a number of other variables that serve as a natural control. This is what is known as a natural experiment: we try to argue that we have made a choice about what to compare that accounts for most alternative explanations.

The death and life of the great American school system: how testing and choice are undermining education by Diane Ravitch

"World Economic Forum" Davos, confounding variable, David Brooks, desegregation, gentrification, hiring and firing, invisible hand, Jane Jacobs, longitudinal study, mega-rich, Menlo Park, Ralph Waldo Emerson, RAND corporation, Robert Gordon, Ronald Reagan, school choice, school vouchers, The Death and Life of Great American Cities

The first school might very well fail to make AYP if it had a student body that was comparable to the one in the second school.”4 State testing systems usually test only once each year, which increases the possibility of random variation. It would help, Linn says, to administer tests at the start of the school year and then again at the end of the school year, to identify the effectiveness of the school. Even then, there would be confounding variables: “For example, students at the school with the higher scores on the state assessment might have received more educational support at home than students at school B. The student bodies attending different schools can differ in many ways that are related to performance on tests, including language background, socioeconomic status, and prior achievement.”5 The professional organizations that set the standards for testing—such as the American Psychological Association and the American Educational Research Association—agree that test results reflect not only what happens in school, but also the characteristics of those tested, including such elusive factors as student motivation and parental engagement.

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Teaching to the test predictably narrows the curriculum and inflates test scores, so it is not a good idea. Similarly, it may be a bad idea to base teacher terminations solely on test score data; the data must be supplemented by evaluations conducted by experienced educators. There are too many other confounding variables. Some states give their tests in midyear—which teacher should receive credit or blame for the students’ scores? The one who taught them for nearly five months last year, or the one who taught them for nearly five months before the test was administered? Districts such as Denver are giving bonuses not only to teachers who bring up their students’ scores, but also to those who agree to work in “hard-to-serve” urban schools or accept “hard-to-staff” assignments (e.g., teachers of special education, middle-school mathematics, and English as a second language), or who improve their knowledge and skills (for instance, by getting an advanced degree in the subject they teach).

The Diet Myth: Why America's Obsessions With Weight Is Hazardous to Your Health by Paul Campos

caloric restriction, caloric restriction, cognitive dissonance, confounding variable, correlation does not imply causation, feminist movement, longitudinal study, moral hazard, moral panic, profit maximization, Saturday Night Live, upwardly mobile

The correlation between the two was—like the vast majority of such correlations—almost wholly coincidental (“almost wholly” because it turns out that a tiny percentage of people own so many clothes that this fact in itself appears to cause such persons to be sedentary). The “disease” of Leviosity, or whatever it had been called, would now be recognized as a largely imaginary phenomenon. Except for the business about the medical profession owning up to its mistakes, the above analogy describes the current state of obesity research. Now that confounding variables such as activity levels are at last being taken into account, researchers have discovered that, except for the most extreme cases, the apparent relationship between body mass and health—which was weak to begin with—is in most instances random. However, there is still a fifty-billion-dollar-per-year industry dedicated to convincing Americans that if they don’t get rid of their blue jeans they will be severely endangering their health.

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These researchers would also turn a skeptical eye on the weight-gaining industry, pointing to the plentiful data that indicated attempts to gain weight did more harm than good, and that many of the health problems suffered by thin people could be traced directly to their unsuccessful efforts to become fatter. Yet the real revolution in emaciation studies would not begin until emaciation researchers started to include confounding variables in their previously simplistic data sets, such as smoking and exercise. Once these factors were taken into account, it would begin to become clear that, contrary to the conventional wisdom, there was actually very little relationship between thinness and poor health, except at the most extreme levels.

The Pot Book: A Complete Guide to Cannabis by Julie Holland

benefit corporation, Berlin Wall, Burning Man, confounding variable, drug harm reduction, intentional community, longitudinal study, Mahatma Gandhi, mandatory minimum, Maui Hawaii, meta-analysis, pattern recognition, phenotype, placebo effect, profit motive, publication bias, RAND corporation, randomized controlled trial, Ronald Reagan, Rosa Parks, Stephen Hawking, traumatic brain injury, University of East Anglia, zero-sum game

A longitudinal follow-up of this sample (Sherrill et al. 1991) confirmed deficits in this same ratio. A study of New Zealanders who smoked cannabis daily or almost daily showed deficits in this same measure (Taylor et al. 2000). A follow-up of this New Zealand sample found that the results were no longer statistically significant once confounding variables were included (Taylor et al. 2002). Only further work can help resolve these conflicting results, though it is my sincere hope that users will turn to safer methods of administration that will make COPD and lung airway problems less likely. BRONCHOSCOPE EXAMINATIONS AND BIOPSIES Another approach to examining pulmonary consequences in marijuana users involves examination with a bronchoscope.

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Potential confounders were addressed in these studies, including other drug use and the question of early psychotic symptoms (Zammit et al. 2002; Arseneault et al. 2004). However, as Weiser and others have pointed out, a two- to threefold increase in risk is not so sizable and could be explained by unrecognized confounding variables (Weiser and Noy 2005b). Finally, there is also the issue of potential publication bias; negative studies that find no association between an exposure and an outcome may be less likely to be published. Biological Plausibility Biological plausibility lends support to the hypothesis of a causal association.

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In one study, the Dunedin cohort (described earlier), an association was found only for the subgroup of older adolescents; there was no correction for baseline depressive symptoms; and the association was only barely statistically significant. Two other studies, which used standard diagnostic criteria for a major episode of depression, found an increase in depression risk of less than 20 percent associated with cannabis use, which might very well be accounted for by unidentified confounding variables. Another study also found just a marginal increase and only in a subgroup. The only study that found a robust increase in risk (fourfold!) evaluated the existence of depressive symptoms (which was not a diagnosis of depression) over only two weeks in individuals with clear abuse of or dependence on cannabis.

Virtual Competition by Ariel Ezrachi, Maurice E. Stucke

"World Economic Forum" Davos, Airbnb, Alan Greenspan, Albert Einstein, algorithmic management, algorithmic trading, Arthur D. Levinson, barriers to entry, behavioural economics, cloud computing, collaborative economy, commoditize, confounding variable, corporate governance, crony capitalism, crowdsourcing, Daniel Kahneman / Amos Tversky, David Graeber, deep learning, demand response, Didi Chuxing, digital capitalism, disintermediation, disruptive innovation, double helix, Downton Abbey, driverless car, electricity market, Erik Brynjolfsson, Evgeny Morozov, experimental economics, Firefox, framing effect, Google Chrome, independent contractor, index arbitrage, information asymmetry, interest rate derivative, Internet of things, invisible hand, Jean Tirole, John Markoff, Joseph Schumpeter, Kenneth Arrow, light touch regulation, linked data, loss aversion, Lyft, Mark Zuckerberg, market clearing, market friction, Milgram experiment, multi-sided market, natural language processing, Network effects, new economy, nowcasting, offshore financial centre, pattern recognition, power law, prediction markets, price discrimination, price elasticity of demand, price stability, profit maximization, profit motive, race to the bottom, rent-seeking, Richard Thaler, ride hailing / ride sharing, road to serfdom, Robert Bork, Ronald Reagan, search costs, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, smart meter, Snapchat, social graph, Steve Jobs, sunk-cost fallacy, supply-chain management, telemarketer, The Chicago School, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, Travis Kalanick, turn-by-turn navigation, two-sided market, Uber and Lyft, Uber for X, uber lyft, vertical integration, Watson beat the top human players on Jeopardy!, women in the workforce, yield management

Under the new paradigm, users may be unable to detect the small but statistically significant change in targeted advertisements (or advertised rates). In a Carnegie Mellon study, all conditions were held equal except one (namely gender or specific sites visited). In this controlled experiment, one can measure the direct impact this one change had. But in our day-to-day reality, there are often too many confounding variables and often no handy benchmark.46 A woman searching the web will not necessarily know to what extent the ads she is seeing differ from those her male counterparts see. She will unlikely ask her male colleagues to report the ads they see and compare the differences. Even if users could detect that they were being targeted with rehab ads (or not being offered advertised opportunities for greater salaries), they may not know why they were being discriminated against.

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Aniko Hannak, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson, “Measuring Price Discrimination and Steering on E-Commerce Web Sites,” Proceedings of the 2014 Conference on Internet Measurement Conference, New York, 5, http://www.ccs.neu.edu/home/cbw/pdf/imc151 -hannak.pdf [noting that they could not “determine why results are being personalized based on the data from real-world users, since there are too many confounding variables attached to each . . . user (e.g., their location, choice of browser, purchase history, etc.)”]. Li Xi v. Apple Inc., 603 F. Supp. 2d 464 (E.D.N.Y. 2009) (dismissing end-users’ Robinson-Patman Act claims when the plaintiffs never alleged that they were “competitors engaged in the business of reselling iPhones, that they are in actual competition with a favored purchaser, or that they even resold or attempted to resell their iPhones”); Matthew A.

Small Wars, Big Data: The Information Revolution in Modern Conflict by Eli Berman, Joseph H. Felter, Jacob N. Shapiro, Vestal Mcintyre

basic income, call centre, centre right, classic study, clean water, confounding variable, crowdsourcing, data science, demand response, drone strike, experimental economics, failed state, George Akerlof, Google Earth, guns versus butter model, HESCO bastion, income inequality, income per capita, information asymmetry, Internet of things, iterative process, land reform, mandatory minimum, minimum wage unemployment, moral hazard, natural language processing, operational security, RAND corporation, randomized controlled trial, Ronald Reagan, school vouchers, statistical model, the scientific method, trade route, Twitter Arab Spring, unemployed young men, WikiLeaks, World Values Survey

Economists Nathan Nunn and Nancy Qian looked at exports of food aid from the United States from 1971 through 2006 and its effects on violence across recipients.89 As in some of the other studies we’ve discussed, to disentangle the effects of one variable on another (here, food aid on violence) the researchers needed a source of exogenous variation in food aid—that is, variation in food aid related to violence only through its effect on conflict, as opposed to food aid that occurred because of violence or because of some confounding variable, such as poor governance, that resulted in both violence and food aid. (In the Philippine CCT example, randomization ensured that exogeneity.) Nunn and Qian found an exogenous force: variation in U.S. wheat production. Wheat is the largest component of U.S. food aid, constituting 58 percent of total assistance over the study period.90 The share of U.S. food aid donated to different countries is politically determined, but the level of overall food aid in any given year is dictated by excess U.S. production.

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The report said, “Kinetic action to counter insurgents can create negative informational effects with the wider population, and thereby lead to strategic losses” (3). Those reports do not pass the causal identification test: the findings of opinion polls, for example, did not control for possible confounding variables, such as response bias. However, it is important and reassuring that military thinkers and practitioners drawing on qualitative evidence come to the same conclusion. 35. “Abdullah Abdullah Pulls out of Afghan Presidential Election Run-off,” Telegraph, 1 November 2009, http://www.telegraph.co.uk/news/worldnews/asia/afghanistan/6478225/Abdullah-Abdullah-pulls-out-of-Afghan-presidential-election-run-off.html, accessed 14 July 2016. 36.

The Numbers Game: The Commonsense Guide to Understanding Numbers in the News,in Politics, and inLife by Michael Blastland, Andrew Dilnot

Atul Gawande, business climate, confounding variable, correlation does not imply causation, credit crunch, happiness index / gross national happiness, Intergovernmental Panel on Climate Change (IPCC), moral panic, pension reform, pensions crisis, randomized controlled trial, school choice, very high income

The results had significant implications for criminal justice and behavior in general, but seem to have been effectively ignored by the Home Office, which refused us an explanation for its unwillingness to support a follow-up trial and finally acquiesced to a new study only in 2008. Yet this comparison had merit. Care was taken to make sure the two groups were as alike as possible so that the risk of there being some lurking difference, what is sometimes known as a confounding variable, was minimized. The selected prisoners were assigned to the two groups at random, without either researchers or subjects knowing who was receiving the real supplement and who was receiving the placebo until afterward, so that any expectations they might have had for the experiment would not be allowed to interfere with the result.

A Mathematician Plays the Stock Market by John Allen Paulos

Alan Greenspan, AOL-Time Warner, Benoit Mandelbrot, Black-Scholes formula, book value, Brownian motion, business climate, business cycle, butter production in bangladesh, butterfly effect, capital asset pricing model, confounding variable, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, dogs of the Dow, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, equity risk premium, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, intangible asset, invisible hand, Isaac Newton, it's over 9,000, John Bogle, John Nash: game theory, Larry Ellison, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Myron Scholes, Nash equilibrium, Network effects, passive investing, Paul Erdős, Paul Samuelson, Plato's cave, Ponzi scheme, power law, price anchoring, Ralph Nelson Elliott, random walk, Reminiscences of a Stock Operator, Richard Thaler, risk free rate, Robert Shiller, short selling, six sigma, Stephen Hawking, stocks for the long run, survivorship bias, transaction costs, two and twenty, ultimatum game, UUNET, Vanguard fund, Yogi Berra

It doesn’t matter if the attributes are ethnicity and hip circumference, or (some measure of) anxiety and hair color, or perhaps the amount of sweet corn consumed annually and the number of mathematics courses taken. Despite the correlation’s statistical significance (its unlikelihood of occurring by chance), it is probably not practically significant because of the presence of so many confounding variables. Furthermore, it will not necessarily support the (often ad hoc) story that accompanies it, the one purporting to explain why people who eat a lot of corn take more math. Superficially plausible tales are always available: Corn-eaters are more likely to be from the upper Midwest, where dropout rates are low.

Arbitrary Lines: How Zoning Broke the American City and How to Fix It by M. Nolan Gray

Albert Einstein, barriers to entry, Black Lives Matter, car-free, carbon footprint, City Beautiful movement, clean water, confounding variable, COVID-19, desegregation, Donald Shoup, Edward Glaeser, Elisha Otis, game design, garden city movement, gentrification, George Floyd, global pandemic, Home mortgage interest deduction, housing crisis, industrial cluster, Jane Jacobs, job-hopping, land bank, lone genius, mass immigration, McMansion, mortgage tax deduction, Overton Window, parking minimums, restrictive zoning, rewilding, San Francisco homelessness, scientific management, Silicon Valley, SimCity, starchitect, streetcar suburb, superstar cities, The Death and Life of Great American Cities, transit-oriented development, Tyler Cowen, Tyler Cowen: Great Stagnation, urban planning, urban renewal, War on Poverty

Nolan Gray) Combined with other planning initiatives, zoning largely succeeded in preserving segregation where it existed and instituting segregation where it didn’t. Indeed, one study finds that cities that adopted zoning between 1900 and 1930 exhibited significantly higher levels of racial and economic segregation in 1970, controlling for a host of potential confounding variables.2 And while racial segregation has slightly moderated since 1970—no thanks to zoning—class segregation has only continued to worsen, with this trend most pronounced in cities with the most restrictive land-use regulations, zoning key among them. Combine this segregation with unequal public service provision and the result is a system of zoning that methodically corrals the most vulnerable Americans into the worst neighborhoods.

The Big Fat Surprise: Why Butter, Meat and Cheese Belong in a Healthy Diet by Nina Teicholz

Albert Einstein, caloric restriction, caloric restriction, confounding variable, correlation coefficient, correlation does not imply causation, Gary Taubes, Indoor air pollution, meta-analysis, phenotype, placebo effect, randomized controlled trial, Robert Gordon, selection bias, TED Talk, the scientific method, Upton Sinclair

It turns out that people who dutifully follow advice are somehow quite different from the sort of people who don’t; maybe they take better care of themselves in general. Maybe they’re richer. But whatever the reason, statisticians generally agree that this compliance effect is quite large. Therefore, any associations found between meat eating and disease, in order to be meaningful, must be big enough to overcome this compliance effect as well as other confounding variables. Yet, like the small association that Harvard researchers found in their 2012 study, the associations seen between red meat consumption and heart disease have generally been minimal, a scientific detail that study leaders tend not to emphasize and that the mainstream media have also, on the whole, overlooked.

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Elderly women in the study did see slightly lower rates of heart disease, however. VI. This “healthy volunteer bias” was acknowledged by the study leaders, who tried to account for it (Fraser, Sabate, and Beeson 1993, 533). VII. Gary Fraser, the epidemiologist at Loma Linda University who has recently led the study (which is ongoing), wrote that these “possible confounding variables” made it difficult to zero in on what, exactly, might be protecting health. He objected, even, to the way that nutrition experts such as William Castelli, then director of the Framingham Study, were exaggerating his study’s results. Castelli claimed that Seventh-day Adventists experienced only “one seventh” the risk of heart attacks of other Americans, but the difference was really only “modest,” corrected Fraser (Fraser 1988; Fraser, Sabaté, and Beeson 1993, 533).

Potatoes not Prozac by Kathleen DesMaisons, Ph. D.

confounding variable, impulse control, meta-analysis, mouse model, selective serotonin reuptake inhibitor (SSRI)

A major constraint of this process is that it takes years to evolve and also depends upon funding that may be affected by a changing political climate. Even more problematic is that science books are about data rather than real people who are living complex, messy lives. Scientists work to exclude the complexity and contradiction of messiness by focusing on one variable at a time, attempting to exclude what are called “confounding variables.” Field clinicians work directly with people rather than simply manipulate numbers. Clinicians are in the trenches of everyday life. When I started the process of looking at the science, I was a clinician in the field of addiction. I brought years of experience to the table. I had worked in mental health, nutrition, and public policy.

Longevity: To the Limits and Beyond (Research and Perspectives in Longevity) by Jean-Marie Robine, James W. Vaupel, Bernard Jeune, Michel Allard

caloric restriction, caloric restriction, classic study, computer age, conceptual framework, confounding variable, demographic transition, Drosophila, epigenetics, life extension, longitudinal study, phenotype, stem cell, stochastic process

This effect is not yet fully explained but there is growing evidence that it involves systemic upregulation of endogenous stress response mechanisms. Similar effects are observed in some invertebrate models and are currently under investigation in primates. The idea that nutritional supplements, e.g., antioxidants, can influence life span has some support and merits further study. It is important that such studies control for confounding variables such as food intake; for example if a nutritional supplement reduces food palatibility, it may result in reduced calorie intake. Discussion From the biological point of view, there would appear not to be a fIxed limit to human life span, even though for practical purposes the longevity of our species is rather well-defIned and may prove resistant to change.

The Great Leveler: Violence and the History of Inequality From the Stone Age to the Twenty-First Century by Walter Scheidel

agricultural Revolution, assortative mating, basic income, Berlin Wall, Bernie Sanders, Branko Milanovic, British Empire, capital controls, Capital in the Twenty-First Century by Thomas Piketty, classic study, collective bargaining, colonial rule, Columbian Exchange, conceptual framework, confounding variable, corporate governance, cosmological principle, CRISPR, crony capitalism, dark matter, declining real wages, democratizing finance, demographic transition, Dissolution of the Soviet Union, Downton Abbey, Edward Glaeser, failed state, Fall of the Berlin Wall, financial deregulation, fixed income, Francisco Pizarro, full employment, Gini coefficient, global pandemic, Great Leap Forward, guns versus butter model, hiring and firing, income inequality, John Markoff, knowledge worker, land reform, land tenure, low skilled workers, means of production, mega-rich, Network effects, nuclear winter, offshore financial centre, plutocrats, race to the bottom, recommendation engine, rent control, rent-seeking, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, Simon Kuznets, synthetic biology, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, transatlantic slave trade, universal basic income, very high income, working-age population, zero-sum game

Economic development and urbanization drove up resource inequality as wealth both expanded and became increasingly unevenly distributed. Detailed registers of wealth taxes that were based on periodic assessments of all urban households serve as a fairly accurate proxy of actual assets and their distribution. Several confounding variables need to be taken into account. Even those residents who were recorded as holding no taxable property would have owned some personal belongings whose inclusion might somewhat reduce measured inequality. At the same time, a general exemption for every household’s first 500 gulden in cash applied—an amount that, taxed at 0.5 percent, was equivalent to a tax payment of 2.5 gulden, or more than anyone below the top fifth of the income distribution paid in 1618.

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Finally, England, which boasted a degree of maldistribution of material resources similar to that found in all these other societies, did not experience any significant domestic upheavals at all. It is tempting to attribute different outcomes to variation in political institutions or performance in war, but the more confounding variables we bring to the table, the more difficult it becomes to apply a coherent endogenizing theory to a wide range of real-life cases. Much work remains to be done.6 ”PEACE FOR OUR TIME”: ALTERNATIVE OUTCOMES This is equally true of my second question. History has its limits. Any historical account of inequality necessarily focuses on what (we think) actually happened and tries to explain why it did.

The No Need to Diet Book: Become a Diet Rebel and Make Friends With Food by Plantbased Pixie

Albert Einstein, confounding variable, David Attenborough, employer provided health coverage, fake news, food desert, meta-analysis, microaggression, nocebo, placebo effect, publication bias, randomized controlled trial, sugar pill, ultra-processed food

A large accumulation of fat cells in the central trunk is more harmful than body fat in other places. Also known as visceral fat, it gathers around the body’s organs, as opposed to subcutaneous fat, which sits under the skin. Increased BMI may be linked to various diseases, I don’t deny that, but causation often cannot be established, and there are a whole host of confounding variables that often don’t get corrected for in research. These include other lifestyle factors such as exercise, nutrition and stress, as well as socio-economic and genetic factors. We cannot categorically say that excess weight causes a lot of disease. When it comes to mortality, that’s where things get interesting.

Testosterone Rex: Myths of Sex, Science, and Society by Cordelia Fine

"World Economic Forum" Davos, assortative mating, behavioural economics, Cass Sunstein, classic study, confounding variable, credit crunch, Donald Trump, Downton Abbey, Drosophila, epigenetics, experimental economics, gender pay gap, George Akerlof, glass ceiling, helicopter parent, Jeremy Corbyn, longitudinal study, meta-analysis, phenotype, publication bias, risk tolerance, seminal paper

Masculinity threats only had an effect on financial decisions made publicly, suggesting that costly displays of masculinity in response to a threat of manhood are only worth it if they serve a face-saving function.48 Although we have to be careful that findings like these are robust and replicable, they have an important implication, as Nelson points out: Differences that may appear at a cursory level to be due to “essential” differences between the sexes may in fact be due (in part or completely) to some additional, confounding variable, such as societal pressures to conform to gender expectations or locations in a social hierarchy of power, or may no longer be seen when the sampling universe is broadened.49 Yet researchers may nonetheless treat results as though they reflect categorical, Mars versus Venus differences, Nelson goes on to point out.

Know Thyself by Stephen M Fleming

Abraham Wald, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, autism spectrum disorder, autonomous vehicles, availability heuristic, backpropagation, citation needed, computer vision, confounding variable, data science, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, Dunning–Kruger effect, Elon Musk, Estimating the Reproducibility of Psychological Science, fake news, global pandemic, higher-order functions, index card, Jeff Bezos, l'esprit de l'escalier, Lao Tzu, lifelogging, longitudinal study, meta-analysis, mutually assured destruction, Network effects, patient HM, Pierre-Simon Laplace, power law, prediction markets, QWERTY keyboard, recommendation engine, replication crisis, self-driving car, side project, Skype, Stanislav Petrov, statistical model, theory of mind, Thomas Bayes, traumatic brain injury

Their loss of metacognition, while real, may be a consequence of changes in other cognitive processes. But if we still find differences in metacognition when other aspects of task performance are well matched between groups or individuals, we can be more confident that we have isolated a change in self-awareness that cannot be explained by other factors. To control for this potential confounding variable, Shimamura needed to find patients with impaired metacognition but intact memory. In a second paper published in 1989, he and his colleagues reported exactly this result. In a group of patients who had suffered damage to their PFC, memory was relatively intact but metacognition was impaired.

Sleepyhead: Narcolepsy, Neuroscience and the Search for a Good Night by Henry Nicholls

A. Roger Ekirch, confounding variable, Donald Trump, double helix, Drosophila, global pandemic, Kickstarter, longitudinal study, meta-analysis, mouse model, placebo effect, Saturday Night Live, stem cell, traumatic brain injury, web application, Yom Kippur War

It’s unsurprising therefore that sleep apnea should increase the risk of cardiovascular disease. The Wisconsin Sleep Study Cohort illustrates this pretty convincingly, a study established in 1988 to try to get a handle on the causes and consequences of having sleep-disordered breathing. When obvious confounding variables like age, sex, body mass index and smoking are controlled for, the greater the apnea-hypopnea score the higher the incidence of coronary heart disease or heart failure. Those in the study with severe sleep apnea were also many times more likely to have died than those with no sleep apnea. Consider this.

The Better Angels of Our Nature: Why Violence Has Declined by Steven Pinker

1960s counterculture, affirmative action, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, availability heuristic, behavioural economics, Berlin Wall, Boeing 747, Bonfire of the Vanities, book value, bread and circuses, British Empire, Broken windows theory, business cycle, California gold rush, Cass Sunstein, citation needed, classic study, clean water, cognitive dissonance, colonial rule, Columbine, computer age, Computing Machinery and Intelligence, conceptual framework, confounding variable, correlation coefficient, correlation does not imply causation, crack epidemic, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, demographic transition, desegregation, Doomsday Clock, Douglas Hofstadter, Dr. Strangelove, Edward Glaeser, en.wikipedia.org, European colonialism, experimental subject, facts on the ground, failed state, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, fudge factor, full employment, Garrett Hardin, George Santayana, ghettoisation, Gini coefficient, global village, Golden arches theory, Great Leap Forward, Henri Poincaré, Herbert Marcuse, Herman Kahn, high-speed rail, Hobbesian trap, humanitarian revolution, impulse control, income inequality, informal economy, Intergovernmental Panel on Climate Change (IPCC), invention of the printing press, Isaac Newton, lake wobegon effect, libertarian paternalism, long peace, longitudinal study, loss aversion, Marshall McLuhan, mass incarceration, McMansion, means of production, mental accounting, meta-analysis, Mikhail Gorbachev, mirror neurons, moral panic, mutually assured destruction, Nelson Mandela, nuclear taboo, Oklahoma City bombing, open economy, Peace of Westphalia, Peter Singer: altruism, power law, QWERTY keyboard, race to the bottom, Ralph Waldo Emerson, random walk, Republic of Letters, Richard Thaler, Ronald Reagan, Rosa Parks, Saturday Night Live, security theater, Skinner box, Skype, Slavoj Žižek, South China Sea, Stanford marshmallow experiment, Stanford prison experiment, statistical model, stem cell, Steven Levy, Steven Pinker, sunk-cost fallacy, technological determinism, The Bell Curve by Richard Herrnstein and Charles Murray, the long tail, The Wealth of Nations by Adam Smith, theory of mind, Timothy McVeigh, Tragedy of the Commons, transatlantic slave trade, trolley problem, Turing machine, twin studies, ultimatum game, uranium enrichment, Vilfredo Pareto, Walter Mischel, WarGames: Global Thermonuclear War, WikiLeaks, women in the workforce, zero-sum game

Two political scientists, Bruce Russett and John Oneal, have breathed new life into the Democratic Peace theory by firming up the definitions, controlling the confounding variables, and testing a quantitative version of the theory: not that democracies never go to war (in which case every putative counterexample becomes a matter of life or death) but that they go to war less often than nondemocracies, all else being equal.223 Russett and Oneal untangled the knot with a statistical technique that separates the effects of confounded variables: multiple logistic regression. Say you discover that heavy smokers have more heart attacks, and you want to confirm that the greater risk was caused by the smoking rather than by the lack of exercise that tends to go with smoking.

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Wilson and George Kelling in their famous Broken Windows theory, was that an orderly environment serves as a reminder that police and residents are dedicated to keeping the peace, whereas a vandalized and unruly one is a signal that no one is in charge.166 Did these bigger and smarter police forces actually drive down crime? Research on this question is the usual social science rat’s nest of confounded variables, but the big picture suggests that the answer is “yes, in part,” even if we can’t pinpoint which of the innovations did the trick. Not only do several analyses suggest that something in the new policing reduced crime, but the jurisdiction that spent the most effort in perfecting its police, New York City, showed the greatest reduction of all.

The End of Illness by David B. Agus

confounding variable, Coronary heart disease and physical activity of work, Danny Hillis, discovery of penicillin, double helix, epigenetics, germ theory of disease, Google Earth, Gregor Mendel, impulse control, information retrieval, Larry Ellison, longitudinal study, Marc Benioff, meta-analysis, Michael Milken, microbiome, Murray Gell-Mann, pattern recognition, Pepto Bismol, personalized medicine, randomized controlled trial, risk tolerance, Salesforce, Steve Jobs, systems thinking, TED Talk, the scientific method

Snowden set out to collect clues about how we can have a better quality of life as we age by following hundreds of nuns who agreed to take mental tests, fill out questionnaires, and donate their brains after they died to be examined for the telltale plaques and tangles that are the definitive diagnosis for Alzheimer’s disease. A common joke among the nuns in the study became a rallying cry: “When we die, our souls will go to heaven, but our brains will go to Kentucky.” The nuns were ideal subjects for the long-term comparative study because they shared such similar life experiences, without confounding variables such as income, pregnancy, or heavy smoking and drinking. In Snowden’s 2001 book, Aging with Grace, which chronicled his experience, he writes that one of the chief messages to be taken from the study is that upbeat attitudes and mentally active lifestyles may offer protection against the onset of implacable, and still mysterious, dementia.

Reset by Ronald J. Deibert

23andMe, active measures, air gap, Airbnb, Amazon Web Services, Anthropocene, augmented reality, availability heuristic, behavioural economics, Bellingcat, Big Tech, bitcoin, blockchain, blood diamond, Brexit referendum, Buckminster Fuller, business intelligence, Cal Newport, call centre, Cambridge Analytica, carbon footprint, cashless society, Citizen Lab, clean water, cloud computing, computer vision, confounding variable, contact tracing, contact tracing app, content marketing, coronavirus, corporate social responsibility, COVID-19, crowdsourcing, data acquisition, data is the new oil, decarbonisation, deep learning, deepfake, Deng Xiaoping, disinformation, Donald Trump, Doomsday Clock, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Evgeny Morozov, failed state, fake news, Future Shock, game design, gig economy, global pandemic, global supply chain, global village, Google Hangouts, Great Leap Forward, high-speed rail, income inequality, information retrieval, information security, Internet of things, Jaron Lanier, Jeff Bezos, John Markoff, Lewis Mumford, liberal capitalism, license plate recognition, lockdown, longitudinal study, Mark Zuckerberg, Marshall McLuhan, mass immigration, megastructure, meta-analysis, military-industrial complex, move fast and break things, Naomi Klein, natural language processing, New Journalism, NSO Group, off-the-grid, Peter Thiel, planetary scale, planned obsolescence, post-truth, proprietary trading, QAnon, ransomware, Robert Mercer, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, single source of truth, Skype, Snapchat, social distancing, sorting algorithm, source of truth, sovereign wealth fund, sparse data, speech recognition, Steve Bannon, Steve Jobs, Stuxnet, surveillance capitalism, techlash, technological solutionism, the long tail, the medium is the message, The Structural Transformation of the Public Sphere, TikTok, TSMC, undersea cable, unit 8200, Vannevar Bush, WikiLeaks, zero day, zero-sum game

It is from studies such as these that we are beginning to understand some of the addictive qualities of our digital experiences (which may help explain the panic you feel when you lose your device). But higher-level effects — e.g., the impact of social media on political polarization or authoritarianism — are far more difficult to untangle from other “confounding variables” (to use the language of social science). Societies are complex, and monocausal theories about them are almost always incorrect. Some of the effects people may attribute to social media — e.g., decline of trust in public institutions — are almost certainly the result of multiple, overlapping factors, some of which reach back decades.

California Burning: The Fall of Pacific Gas and Electric--And What It Means for America's Power Grid by Katherine Blunt

An Inconvenient Truth, benefit corporation, buy low sell high, California energy crisis, call centre, commoditize, confounding variable, coronavirus, corporate personhood, COVID-19, electricity market, Elon Musk, forensic accounting, Google Earth, high-speed rail, junk bonds, lock screen, market clearing, market design, off-the-grid, price stability, rolling blackouts, Silicon Valley, vertical integration

* * * For a two-week stretch in June, the jury heard from a parade of witnesses, first federal pipeline regulators and then PG&E employees. The prosecution flashed evidence of the company’s poor record keeping and haphazard approach to managing changes in pipeline pressure. Bauer scored points on cross-examination, homing in on the many confounding variables that muddied the case. Then, on the morning of July 7, the defense’s hope for victory began to fade. The jury filed into the courtroom to find Bill Manegold, a lifelong engineer who had spent thirty-five years at PG&E. He had retired in 2014 after nearly a decade within the gas division supervising transmission operations.

What’s Your Type? by Merve Emre

Albert Einstein, anti-communist, behavioural economics, card file, confounding variable, correlation does not imply causation, emotional labour, fake news, Frederick Winslow Taylor, Gabriella Coleman, God and Mammon, Golden Gate Park, hiring and firing, Ida Tarbell, index card, Isaac Newton, job satisfaction, late capitalism, Lewis Mumford, means of production, Menlo Park, mutually assured destruction, Norman Mailer, p-value, Panopticon Jeremy Bentham, planned obsolescence, Ralph Waldo Emerson, scientific management, Socratic dialogue, Stanford prison experiment, traveling salesman, upwardly mobile, uranium enrichment, women in the workforce

Gone were the nights spent hunched over her Monroe calculator, the hand-crank adding machine she kept in her living room next to the moldering stacks of answer keys she had accumulated over the previous decade. Gone too was the haphazard, if intimate, research program that had defined the indicator’s early days. For Isabel, the typing of friends and family members had proceeded without controlling for any of the confounding variables that would differentiate introversion and extraversion, sensing and intuiting, thinking and feeling, judging and perceiving, from the other factors that determined an individual’s personality: age, gender, economic status, education, political orientation. “Neither of these authors has had formal training in psychology, and consequently little of the very extensive evidence they have developed on the instrument is in a form for immediate assimilation by psychologists generally,” Chauncey warned his staff as he prepared them to start work on the indicator.

Why We Drive: Toward a Philosophy of the Open Road by Matthew B. Crawford

1960s counterculture, Airbus A320, airport security, augmented reality, autonomous vehicles, behavioural economics, Bernie Sanders, Big Tech, Boeing 737 MAX, British Empire, Burning Man, business logic, call centre, classic study, collective bargaining, confounding variable, congestion pricing, crony capitalism, data science, David Sedaris, deskilling, digital map, don't be evil, Donald Trump, driverless car, Elon Musk, emotional labour, en.wikipedia.org, Fellow of the Royal Society, Ford Model T, gamification, gentrification, gig economy, Google Earth, Great Leap Forward, Herbert Marcuse, hive mind, Ian Bogost, income inequality, informal economy, Internet of things, Jane Jacobs, labour mobility, Lyft, mirror neurons, Network effects, New Journalism, New Urbanism, Nicholas Carr, planned obsolescence, Ponzi scheme, precautionary principle, Ralph Nader, ride hailing / ride sharing, Ronald Reagan, Sam Peltzman, security theater, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, social graph, social intelligence, Stephen Hawking, surveillance capitalism, tacit knowledge, tech worker, technoutopianism, the built environment, The Death and Life of Great American Cities, the High Line, time dilation, too big to fail, traffic fines, Travis Kalanick, trolley problem, Uber and Lyft, Uber for X, uber lyft, Unsafe at Any Speed, urban planning, Wall-E, Works Progress Administration

Crawford didn’t know much about rats but Kelly Lambert, her colleague in the psychology department at the University of Richmond, did, so the two of them teamed up. According to Lambert, we have no idea what rats are capable of because rat research has always been conducted in a highly controlled lab environment, the point of which is to study the effect of one variable and eliminate confounding variables as much as possible. But it is precisely the richness of an animal’s environment that calls forth its evolved capacities, many of which depend on a process of development (during the rat’s own lifetime) in a natural setting no less than the selection pressures that have shaped the species over generations.

Doing Data Science: Straight Talk From the Frontline by Cathy O'Neil, Rachel Schutt

Amazon Mechanical Turk, augmented reality, Augustin-Louis Cauchy, barriers to entry, Bayesian statistics, bike sharing, bioinformatics, computer vision, confounding variable, correlation does not imply causation, crowdsourcing, data science, distributed generation, Dunning–Kruger effect, Edward Snowden, Emanuel Derman, fault tolerance, Filter Bubble, finite state, Firefox, game design, Google Glasses, index card, information retrieval, iterative process, John Harrison: Longitude, Khan Academy, Kickstarter, machine translation, Mars Rover, Nate Silver, natural language processing, Netflix Prize, p-value, pattern recognition, performance metric, personalized medicine, pull request, recommendation engine, rent-seeking, selection bias, Silicon Valley, speech recognition, statistical model, stochastic process, tacit knowledge, text mining, the scientific method, The Wisdom of Crowds, Watson beat the top human players on Jeopardy!, X Prize

In fact, you should have very good evidence that stratification helps before you decide to do it. What Do People Do About Confounding Things in Practice? In spite of the raised objections, experts in this field essentially use stratification as a major method to working through studies. They deal with confounding variables, or rather variables they deem potentially confounding, by stratifying with respect to them or make other sorts of model-based adjustments, such as propensity score matching, for example. So if taking aspirin is believed to be a potentially confounding factor, they adjust or stratify with respect to it.

Rich White Men: What It Takes to Uproot the Old Boys' Club and Transform America by Garrett Neiman

"World Economic Forum" Davos, Affordable Care Act / Obamacare, Albert Einstein, basic income, Bernie Sanders, BIPOC, Black Lives Matter, Branko Milanovic, British Empire, Capital in the Twenty-First Century by Thomas Piketty, carried interest, clean water, confounding variable, coronavirus, COVID-19, critical race theory, dark triade / dark tetrad, data science, Donald Trump, drone strike, effective altruism, Elon Musk, gender pay gap, George Floyd, glass ceiling, green new deal, high net worth, Home mortgage interest deduction, Howard Zinn, impact investing, imposter syndrome, impulse control, income inequality, Jeff Bezos, Jeffrey Epstein, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge worker, Larry Ellison, liberal capitalism, Lyft, Mahatma Gandhi, mandatory minimum, Mark Zuckerberg, mass incarceration, means of production, meritocracy, meta-analysis, Michael Milken, microaggression, mortgage tax deduction, move fast and break things, Nelson Mandela, new economy, obamacare, occupational segregation, offshore financial centre, Paul Buchheit, Peter Thiel, plutocrats, Ralph Waldo Emerson, randomized controlled trial, rent-seeking, Ronald Reagan, Rutger Bregman, Sheryl Sandberg, Silicon Valley, Snapchat, sovereign wealth fund, Steve Jobs, subprime mortgage crisis, TED Talk, The Bell Curve by Richard Herrnstein and Charles Murray, Travis Kalanick, trickle-down economics, uber lyft, universal basic income, Upton Sinclair, War on Poverty, white flight, William MacAskill, winner-take-all economy, women in the workforce, work culture , working poor

The glass cliff phenomenon may also apply to entire fields. In 2017, the Association of American Medical Colleges found that, for the first time, women represented the majority of medical school matriculants.21 The finding was rightly heralded as a win for gender equality. However, there are also some confounding variables. The medical profession is not as lucrative as it used to be: the pay is still good, but the increase in expenses associated with becoming a doctor—like medical school tuition and malpractice insurance—is far outpacing inflation.22 What finally tipped the scale was not only that female applications grew by 10 percent but also that male applications dropped by 2 percent.

Democracy and Prosperity: Reinventing Capitalism Through a Turbulent Century by Torben Iversen, David Soskice

Andrei Shleifer, assortative mating, augmented reality, barriers to entry, Big Tech, Bretton Woods, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, central bank independence, centre right, clean tech, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, confounding variable, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, deindustrialization, deskilling, Donald Trump, first-past-the-post, full employment, general purpose technology, gentrification, Gini coefficient, hiring and firing, implied volatility, income inequality, industrial cluster, inflation targeting, invisible hand, knowledge economy, labor-force participation, liberal capitalism, low skilled workers, low-wage service sector, means of production, middle-income trap, mirror neurons, mittelstand, Network effects, New Economic Geography, new economy, New Urbanism, non-tariff barriers, Occupy movement, offshore financial centre, open borders, open economy, passive investing, precariat, race to the bottom, radical decentralization, rent-seeking, RFID, road to serfdom, Robert Bork, Robert Gordon, Silicon Valley, smart cities, speech recognition, tacit knowledge, The Future of Employment, The Great Moderation, The Rise and Fall of American Growth, the strength of weak ties, too big to fail, trade liberalization, union organizing, urban decay, vertical integration, Washington Consensus, winner-take-all economy, working-age population, World Values Survey, young professional, zero-sum game

Of course, there are many potential confounders, but it is hard to think of any with a more clearly specified micrologic (consistent with our other evidence). The most obvious candidate would be GDP per capita, but while it has a borderline statistically significant negative effect (not shown), it has no effect on the finding for educational opportunity. Other potentially confounding variables such as occupational structure are already controlled for at the individual level, and we can confirm this by including industrial employment shares as a macrovariable: it has no effect. No other argument we are aware of explains the cross-national pattern observed in the data. In concluding this section, we would like to draw attention to the remarkable fact that countries with relatively weak populist sentiments are often noted for having strong populist parties, and vice versa.

Food Allergy: Adverse Reactions to Foods and Food Additives by Dean D. Metcalfe

active measures, Albert Einstein, autism spectrum disorder, bioinformatics, classic study, confounding variable, epigenetics, Helicobacter pylori, hygiene hypothesis, impulse control, life extension, longitudinal study, meta-analysis, mouse model, pattern recognition, phenotype, placebo effect, randomized controlled trial, Recombinant DNA, selection bias, statistical model, stem cell, twin studies, two and twenty

Atherton et al. [38] showed that 14 of 20 subjects (70%) with AD between the ages of 2 and 8 years showed significant improvement after completing a 12-week, double-blind, controlled, crossover trial of an egg and cow’s milk (CM) exclusion diet. However, there were notable problems in this study, including 16 of the 36 subjects who did not complete the study (44% dropout) and poor control of confounding variables such as environmental factors and other triggers of AD. Neild et al. [39] studied 53 subjects with AD in another trial using a similar design as Atherton and colleagues. Forty of the 53 subjects (75%) complied adequately with the trial regimen, but only 10 of the 40 subjects benefited from the egg and CM exclusion diet, yielding a response rate to the diet that was not statistically significant.

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In practice, reporting of results often varies by investigator and may be reported as mean diameter, mean diameter compared to histamine control categorically (e.g. 1⫹, 2⫹, etc.), or as a calculated area. Studies must be evaluated carefully because individual investigators may be reporting data based on a variety of methods that may not be directly comparable (e.g. mean wheal diameter versus largest diameter). Despite the numerous potential confounding variables involved in the PST procedure, the clinical utility is excellent. Technical issues that can impact PST sensitivity are summarized in Table 20.2. Diagnostic value The ability of a test to indicate the presence or absence of disease depends on intrinsic characteristics of the test itself and also features of the population on which it is being applied.

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Arshad et al. [48] in a study of 120 infants randomized participants to either a prophylactic group (breast-fed with mother on a low allergen diet or given an extensively hydrolyzed formula and house dust mite reduction) or a control group (who followed standard UK DoH advice). Findings demonstrate a reduction in allergic disease (asthma, atopy, rhinitis, and eczema) at least for the first 8 years of life in the prophylactic group. Repeated measurement analysis, adjusted for all relevant confounding variables, confirmed a preventive effect on asthma, AD, rhinitis, and atopy. The protective effects were primarily observed in the subgroup of children with persistent disease (symptoms at all visits) and in those with evidence of allergic sensitization. Study powering did not allow for the assessment of food allergy at 8 years of age, but earlier transient effects were noted.

Wool Omnibus Edition by Hugh Howey

back-to-the-land, clean tech, confounding variable, hydroponic farming, invisible hand, long peace

Someone or some thing was always at fault. She knew to listen, to observe, to ask questions of anyone who could have had anything to do with the faulty equipment or the tools that had served the equipment, following a chain of events all the way down to the bedrock itself. There were always confounding variables—you couldn’t adjust one dial without sending something else a-kilter—but Juliette had a skill, a talent, for knowing what was important and what could be ignored. She assumed it was this talent that Deputy Marnes had originally seen in her, this patience and skepticism she employed to ask one more stupid question and stumble eventually onto the answer.

Safe Food: The Politics of Food Safety by Marion Nestle

Asilomar, biofilm, butterfly effect, clean water, confounding variable, double helix, Fellow of the Royal Society, illegal immigration, out of africa, precautionary principle, Ralph Nader, Recombinant DNA, Ronald Reagan, software patent, Upton Sinclair

The quality of scientific research depends not only on the question under investigation (some research questions are more interesting and important than others) and the care (“rigor”) with which studies are conducted, but also on the ability of the studies to eliminate (“control for”) all possible causes of the observation other than the one being tested. Scientific methods also extend beyond observations to suggest probable causes, to exclude irrelevant causes (“confounding variables”), and to estimate the probability that a particular cause is the true reason for the observation of interest. The point here is that probability is not the same as proof. Biological experiments in humans are complicated by genetic variation and behavioral differences, and study results nearly always depend on probabilities and statistics.

The 4-Hour Body: An Uncommon Guide to Rapid Fat-Loss, Incredible Sex, and Becoming Superhuman by Timothy Ferriss

23andMe, airport security, Albert Einstein, Black Swan, Buckminster Fuller, caloric restriction, caloric restriction, carbon footprint, cognitive dissonance, Columbine, confounding variable, correlation does not imply causation, Dean Kamen, game design, Gary Taubes, Gregor Mendel, index card, Kevin Kelly, knowledge economy, language acquisition, life extension, lifelogging, Mahatma Gandhi, messenger bag, microbiome, microdosing, p-value, Paradox of Choice, Parkinson's law, Paul Buchheit, placebo effect, Productivity paradox, publish or perish, radical life extension, Ralph Waldo Emerson, Ray Kurzweil, Recombinant DNA, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Silicon Valley startup, Skype, stem cell, Steve Jobs, sugar pill, survivorship bias, TED Talk, The future is already here, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Vilfredo Pareto, wage slave, William of Occam

It isn’t quite that easy. I also started cold treatments and supplemental selenium (Brazil nuts), both of which could have contributed, the latter more likely than the former. Do I care about the academic purity? No. I was more concerned with increasing sperm count than isolating variables. Even with two confounding variables, the experiment is directionally valid. Should you wait for a scientific consensus? I don’t think so. This is a case where the current literature is strong enough, and the inconvenience minimal enough, to not wait for doctor’s orders. It can’t hurt you, and it might get your swim team off the bench and back in the game.

Adaptive Markets: Financial Evolution at the Speed of Thought by Andrew W. Lo

Alan Greenspan, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Andrei Shleifer, Arthur Eddington, Asian financial crisis, asset allocation, asset-backed security, backtesting, bank run, barriers to entry, Bear Stearns, behavioural economics, Berlin Wall, Bernie Madoff, bitcoin, Bob Litterman, Bonfire of the Vanities, bonus culture, break the buck, Brexit referendum, Brownian motion, business cycle, business process, butterfly effect, buy and hold, capital asset pricing model, Captain Sullenberger Hudson, carbon tax, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, confounding variable, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Daniel Kahneman / Amos Tversky, delayed gratification, democratizing finance, Diane Coyle, diversification, diversified portfolio, do well by doing good, double helix, easy for humans, difficult for computers, equity risk premium, Ernest Rutherford, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, financial intermediation, fixed income, Flash crash, Fractional reserve banking, framing effect, Glass-Steagall Act, global macro, Gordon Gekko, greed is good, Hans Rosling, Henri Poincaré, high net worth, housing crisis, incomplete markets, index fund, information security, interest rate derivative, invention of the telegraph, Isaac Newton, it's over 9,000, James Watt: steam engine, Jeff Hawkins, Jim Simons, job satisfaction, John Bogle, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, Joseph Schumpeter, Kenneth Rogoff, language acquisition, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, Louis Pasteur, mandelbrot fractal, margin call, Mark Zuckerberg, market fundamentalism, martingale, megaproject, merger arbitrage, meta-analysis, Milgram experiment, mirror neurons, money market fund, moral hazard, Myron Scholes, Neil Armstrong, Nick Leeson, old-boy network, One Laptop per Child (OLPC), out of africa, p-value, PalmPilot, paper trading, passive investing, Paul Lévy, Paul Samuelson, Paul Volcker talking about ATMs, Phillips curve, Ponzi scheme, predatory finance, prediction markets, price discovery process, profit maximization, profit motive, proprietary trading, public intellectual, quantitative hedge fund, quantitative trading / quantitative finance, RAND corporation, random walk, randomized controlled trial, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Robert Shiller, Robert Solow, Sam Peltzman, Savings and loan crisis, seminal paper, Shai Danziger, short selling, sovereign wealth fund, Stanford marshmallow experiment, Stanford prison experiment, statistical arbitrage, Steven Pinker, stochastic process, stocks for the long run, subprime mortgage crisis, survivorship bias, systematic bias, Thales and the olive presses, The Great Moderation, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, Tobin tax, too big to fail, transaction costs, Triangle Shirtwaist Factory, ultimatum game, uptick rule, Upton Sinclair, US Airways Flight 1549, Walter Mischel, Watson beat the top human players on Jeopardy!, WikiLeaks, Yogi Berra, zero-sum game

., 309–310 Cohn, Alain, 352–353 Cold War, 52 collateralized debt obligations (CDOs), 298, 299, 343 Collier, Paul, 412 Colossal Failure of Common Sense, A (McDonald and Robinson), 317–318 commercial banks, 293, 301, 308, 335, 371 commodities trading, 20, 34 Commodity Futures Trading Commission (CFTC), 359, 360, 377 common law, 372 competition, 3, 153, 168, 214, 217 complexity, 217, 278, 361–364, 372, 374 computational biochemistry, 240 computerized axial tomography (CAT), 78, 102 confirmation bias, 305–306 confounding variables, 139 congenital analgesia, 378 Congo Free State, 412 consilience, 215 Consolidated Supervised Entities, 306 contrarian strategy, 290, 316, 325 controlled experiments, 47, 139 Cook, William, 236 cooperation, 164–165, 168, 214, 336, 340 Coppersmith, Don, 239 core, in networks, 374–376 corn, 28–29, 30 corpus callosum, 113–114 Cortana, 396 cortex, 81, 130; anterior cingulate, 86, 105; prefrontal, see prefrontal cortex cortisol, 81 Cosmides, Leda, 173, 174 cost-benefit analysis, 104, 119, 121–122, 169, 316 Cost Matters Hypothesis, 265, 397 Cotzias, George, 88 Countrywide Financial, 325 coupling, 321–322, 361, 372–374 creative destruction, 219 credit default swaps (CDSs), 298, 300, 379, 407 credit rating agencies, 301 Crick, Francis, 137, 144, 401 Cronqvist, Henrik, 161 crowded trades, 291–292, 293 crowdfunding, 356 cryptography, 238–239, 385 currency trading, 12–16, 24, 38 D.

The 4-Hour Chef: The Simple Path to Cooking Like a Pro, Learning Anything, and Living the Good Life by Timothy Ferriss

Airbnb, Atul Gawande, Blue Bottle Coffee, Buckminster Fuller, Burning Man, confounding variable, correlation does not imply causation, crowdsourcing, deliberate practice, digital nomad, en.wikipedia.org, Golden Gate Park, happiness index / gross national happiness, haute cuisine, Hugh Fearnley-Whittingstall, Isaac Newton, Johann Wolfgang von Goethe, Kevin Kelly, Kickstarter, language acquisition, Loma Prieta earthquake, loss aversion, Louis Pasteur, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, microbiome, off-the-grid, Parkinson's law, Paul Buchheit, Paul Graham, Pepsi Challenge, Pepto Bismol, Ponzi scheme, Ralph Waldo Emerson, San Francisco homelessness, Silicon Valley, Skype, spaced repetition, Stephen Hawking, Steve Jobs, TED Talk, the High Line, Y Combinator

For those of you who want to “go beyond” in your research, I have provided links to Internet resources. My team and I have worked to check that these links are accurate and point to resources available when this book was released for publication. But Internet resources change frequently, and other confounding variables beyond my control intervene. So, for various reasons, the links may not direct you to the resource I had intended. In many cases, you will likely be able to use your favorite search engine to locate the correct link. Where links to a good resource are not working, and avid readers among you let me know, we will work to provide updated and corrected links in posts or pages at fourhourblog.com.

Enlightenment Now: The Case for Reason, Science, Humanism, and Progress by Steven Pinker

3D printing, Abraham Maslow, access to a mobile phone, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, Alignment Problem, An Inconvenient Truth, anti-communist, Anton Chekhov, Arthur Eddington, artificial general intelligence, availability heuristic, Ayatollah Khomeini, basic income, Berlin Wall, Bernie Sanders, biodiversity loss, Black Swan, Bonfire of the Vanities, Brexit referendum, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, Charlie Hebdo massacre, classic study, clean water, clockwork universe, cognitive bias, cognitive dissonance, Columbine, conceptual framework, confounding variable, correlation does not imply causation, creative destruction, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, data science, decarbonisation, degrowth, deindustrialization, dematerialisation, demographic transition, Deng Xiaoping, distributed generation, diversified portfolio, Donald Trump, Doomsday Clock, double helix, Eddington experiment, Edward Jenner, effective altruism, Elon Musk, en.wikipedia.org, end world poverty, endogenous growth, energy transition, European colonialism, experimental subject, Exxon Valdez, facts on the ground, fake news, Fall of the Berlin Wall, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, frictionless, frictionless market, Garrett Hardin, germ theory of disease, Gini coefficient, Great Leap Forward, Hacker Conference 1984, Hans Rosling, hedonic treadmill, helicopter parent, Herbert Marcuse, Herman Kahn, Hobbesian trap, humanitarian revolution, Ignaz Semmelweis: hand washing, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), invention of writing, Jaron Lanier, Joan Didion, job automation, Johannes Kepler, John Snow's cholera map, Kevin Kelly, Khan Academy, knowledge economy, l'esprit de l'escalier, Laplace demon, launch on warning, life extension, long peace, longitudinal study, Louis Pasteur, Mahbub ul Haq, Martin Wolf, mass incarceration, meta-analysis, Michael Shellenberger, microaggression, Mikhail Gorbachev, minimum wage unemployment, moral hazard, mutually assured destruction, Naomi Klein, Nate Silver, Nathan Meyer Rothschild: antibiotics, negative emissions, Nelson Mandela, New Journalism, Norman Mailer, nuclear taboo, nuclear winter, obamacare, ocean acidification, Oklahoma City bombing, open economy, opioid epidemic / opioid crisis, paperclip maximiser, Paris climate accords, Paul Graham, peak oil, Peter Singer: altruism, Peter Thiel, post-truth, power law, precautionary principle, precision agriculture, prediction markets, public intellectual, purchasing power parity, radical life extension, Ralph Nader, randomized controlled trial, Ray Kurzweil, rent control, Republic of Letters, Richard Feynman, road to serfdom, Robert Gordon, Rodney Brooks, rolodex, Ronald Reagan, Rory Sutherland, Saturday Night Live, science of happiness, Scientific racism, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Kuznets, Skype, smart grid, Social Justice Warrior, sovereign wealth fund, sparse data, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, Stewart Brand, Stuxnet, supervolcano, synthetic biology, tech billionaire, technological determinism, technological singularity, Ted Kaczynski, Ted Nordhaus, TED Talk, The Rise and Fall of American Growth, the scientific method, The Signal and the Noise by Nate Silver, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, total factor productivity, Tragedy of the Commons, union organizing, universal basic income, University of East Anglia, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, urban renewal, W. E. B. Du Bois, War on Poverty, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y2K

The developing world has thrived in that realm as well, often leapfrogging the West in its adoption of smartphones and of applications for them such as mobile banking, education, and real-time market updates.41 Could the Flynn effect help explain the other rises in well-being we have seen in these chapters? An analysis by the economist R. W. Hafer suggests it could. Holding all the usual confounding variables constant—education, GDP, government spending, even a country’s religious makeup and its history of colonization—he found that a country’s average IQ predicted its subsequent growth in GDP per capita, together with growth in noneconomic measures of well-being like longevity and leisure time.

Theory and Practice of Group Psychotherapy by Irvin D. Yalom, Molyn Leszcz

cognitive dissonance, conceptual framework, confounding variable, delayed gratification, deskilling, epigenetics, experimental subject, impulse control, meta-analysis, randomized controlled trial, TED Talk, the scientific method, traveling salesman, unbiased observer

To do so thrusts the individual into a state of uncomfortable dissonance. Research on marathon groups is plagued with a multitude of design defects. 16 Some studies failed to employ proper controls (for example, a non–time-extended comparison group). Others failed to sort out the effects of artifact and other confounding variables. For example, in a residential community of drug addicts, an annual marathon group was offered to rape survivors. Because the group was offered only once a year, the participants imbued it with value even before it took place.17 The rigorous controlled studies comparing differences in outcome between time-extended and non–time-extended groups conclude that there is no evidence for the efficacy of the time-extended format.

Ashes to Ashes: America's Hundred-Year Cigarette War, the Public Health, and the Unabashed Triumph of Philip Morris by Richard Kluger

air freight, Albert Einstein, book value, California gold rush, cognitive dissonance, confounding variable, corporate raider, desegregation, disinformation, double entry bookkeeping, family office, feminist movement, full employment, ghettoisation, independent contractor, Indoor air pollution, junk bonds, medical malpractice, Mikhail Gorbachev, plutocrats, power law, publication bias, Ralph Nader, Ralph Waldo Emerson, RAND corporation, rent-seeking, risk tolerance, Ronald Reagan, selection bias, stock buybacks, The Chicago School, the scientific method, Torches of Freedom, trade route, transaction costs, traveling salesman, union organizing, upwardly mobile, urban planning, urban renewal, vertical integration, War on Poverty

But the committee’s sense of duty went further and was perhaps best exemplified by the attentive ear that staff director Hamill gave to the industry’s chief scientific representative, Clarence Little, who at seventy-five was performing his final well-paid services for the tobacco manufacturers. He was seeking assurance that the Surgeon General’s panelists would take into account all the possibly confounding variables in the evidence before them. He and Hamill proceeded as wary performers, if not open antagonists, in a high drama, with Hamill recognizing what he called Little’s “blind spot”—an almost dismissive attitude toward the laws of statistics and probability. “You had to see a thing happen in the laboratory to convince him it was true,” Hamill recalled of their exchanges.