fudge factor

43 results back to index


pages: 258 words: 73,109

The (Honest) Truth About Dishonesty: How We Lie to Everyone, Especially Ourselves by Dan Ariely

accounting loophole / creative accounting, Albert Einstein, Bernie Madoff, Broken windows theory, cashless society, clean water, cognitive dissonance, Credit Default Swap, Donald Trump, fudge factor, new economy, Richard Feynman, Schrödinger's Cat, Shai Danziger, shareholder value, Steve Jobs, Walter Mischel

If your accountant were to ask you to sign an honor code a moment before filing your taxes or if your insurance agent made you swear that you were telling the whole truth about that water-damaged furniture, chances are that tax evasion and insurance fraud would be less common.* What are we to make of all this? First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this stand-point—from banking practices to backdating stock options, from defaulting on loans and mortgages to cheating on taxes—there’s a lot more to honesty and dishonesty than rational calculations.

How can we secure the benefits of cheating and at the same time still view ourselves as honest, wonderful people? This is where our amazing cognitive flexibility comes into play. Thanks to this human skill, as long as we cheat by only a little bit, we can benefit from cheating and still view ourselves as marvelous human beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear decisions you had to make? Would it be legitimate to write off a portion of your car repair as a business expense? If so, what amount would you feel comfortable with? And what if you had a second car? I’m not talking about justifying our decisions to the Internal Revenue Service (IRS); I’m talking about the way we are able to justify our exaggerated level of tax deductions to ourselves.

Although most people haven’t consciously figured out (much less announced) their acceptable rate of lying like this young man, this overall approach seems to be quite accurate; each of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole a pencil from the student sitting next to him.” Jimmy’s father is furious. He goes to great lengths to lecture Jimmy and let him know how upset and disappointed he is, and he grounds the boy for two weeks.


pages: 898 words: 266,274

The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, assortative mating, banking crisis, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, computer vision, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, end world poverty, endowment effect, Exxon Valdez, first-price auction, Frederick Winslow Taylor, fudge factor, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, new economy, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skype, software as a service, Steve Jobs, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, ultimatum game, Upton Sinclair, Walter Mischel, young professional

If your accountant were to ask you to sign an honor code a moment before filing your taxes or if your insurance agent made you swear that you were telling the whole truth about that water-damaged furniture, chances are that tax evasion and insurance fraud would be less common.* What are we to make of all this? First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this standpoint—from banking practices to backdating stock options, from defaulting on loans and mortgages to cheating on taxes—there’s a lot more to honesty and dishonesty than rational calculations.

How can we secure the benefits of cheating and at the same time still view ourselves as honest, wonderful people? This is where our amazing cognitive flexibility comes into play. Thanks to this human skill, as long as we cheat by only a little bit, we can benefit from cheating and still view ourselves as marvelous human beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear decisions you had to make? Would it be legitimate to write off a portion of your car repair as a business expense? If so, what amount would you feel comfortable with? And what if you had a second car? I’m not talking about justifying our decisions to the Internal Revenue Service (IRS); I’m talking about the way we are able to justify our exaggerated level of tax deductions to ourselves.

Although most people haven’t consciously figured out (much less announced) their acceptable rate of lying like this young man, this overall approach seems to be quite accurate; each of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole a pencil from the student sitting next to him.” Jimmy’s father is furious. He goes to great lengths to lecture Jimmy and let him know how upset and disappointed he is, and he grounds the boy for two weeks.


Elliptic Tales: Curves, Counting, and Number Theory by Avner Ash, Robert Gross

Andrew Wiles, fudge factor, Georg Cantor, P = NP

Now we can define the Hasse–Weil zeta-function of C, denoted Z(C, s), except for a certain fudge factor we will explain but not define. You simply substitute T = p−s in ζC,p (T) and then multiply all these local factors together: Z(C, s) = ζC,p (p−s ) × fudge. p good Here is a rough idea of where the fudge factor comes from. We call a prime p “good” for C if C modulo p is nonsingular, which means C(Fac p ) has no ac singular point on it, where Fp is as usual an algebraic closure of Fp . We call p “bad” if it is not good. For a given curve C, there are only a finite number of bad primes. The factor called “fudge” is a product of certain functions of p−s for the bad primes p. These functions are defined in a complicated way we can’t go into here. (However, when C is an elliptic curve, we will be able to tell you how to define the fudge factors.) The fudge factors are hard to define, but they are essential to flesh out our understanding of C modulo p for all primes p.

The numerator of the Hasse–Weil zetafunction of C is the product over good primes of polynomials of degree 2g evaluated at p−s , times a fudge factor from the bad primes. The reciprocal of this numerator is called the L-function of C, and is written L(C, s). In the case of a curve, we have the formula L(C, s) = fudge × p good 1 , fp (p−s ) where fp (T) is some polynomial of degree 2g. The theory tells us that the constant term of fp is always equal to 1, and various theorems give us bounds on the absolute values of the coefficients of fp . So we can write this as L(C, s) = fudge × 1 p good 1 + c1,p p−s + c2,p p−2s + · · · + c2g,p p−2gs . (Remember that although we don’t say here what the fudge factor is, it is known and can be determined.) Using long division for each term in the product, divide the denominator into 1, and you will get a series in powers of p−s , just as you do when dealing with the Riemann zeta-function.

The bounds on the absolute values of the coefficients of fp can be used to prove that this Dirichlet series 207 L- FUNCTIONS converges in some right half-plane, as all Dirichlet series with number theoretic significance ought to do. 4. The L-Function of an Elliptic Curve In this section, we will carry out the details of constructing the L-function of an elliptic curve E defined over Q. In this case, we can even say what the fudge factors are. In this section, and for the remainder of this book, we use the so-called “minimal model” for E. This is an equation for E with smallest possible |E | chosen among all possible equations defining E. Using the minimal model allows us to specify the fudge factors correctly. Recall from chapter 8 that E (mod p) is an elliptic curve defined over Fp for any p not dividing the discriminant E . That is, E modulo p is still a nonsingular projective curve, with E(Fp ) nonempty, because the point at infinity on E will always reduce to a point modulo p.


Principles of Corporate Finance by Richard A. Brealey, Stewart C. Myers, Franklin Allen

3Com Palm IPO, accounting loophole / creative accounting, Airbus A320, Asian financial crisis, asset allocation, asset-backed security, banking crisis, Bernie Madoff, big-box store, Black-Scholes formula, break the buck, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, carried interest, collateralized debt obligation, compound rate of return, computerized trading, conceptual framework, corporate governance, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-subsidies, discounted cash flows, disintermediation, diversified portfolio, equity premium, eurozone crisis, financial innovation, financial intermediation, fixed income, frictionless, fudge factor, German hyperinflation, implied volatility, index fund, information asymmetry, intangible asset, interest rate swap, inventory management, Iridium satellite, Kenneth Rogoff, law of one price, linear programming, Livingstone, I presume, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, market friction, money market fund, moral hazard, Myron Scholes, new economy, Nick Leeson, Northern Rock, offshore financial centre, Ponzi scheme, prediction markets, price discrimination, principal–agent problem, profit maximization, purchasing power parity, QR code, quantitative trading / quantitative finance, random walk, Real Time Gross Settlement, risk tolerance, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, Silicon Valley, Skype, Steve Jobs, The Nature of the Firm, the payments system, the rule of 72, time value of money, too big to fail, transaction costs, University of East Anglia, urban renewal, VA Linux, value at risk, Vanguard fund, yield curve, zero-coupon bond, zero-sum game, Zipcar

Step 2 is to consider whether diversified investors would regard the project as more or less risky than the average project. In this step only market risks are relevant. Avoid Fudge Factors in Discount Rates Think back to our example of project Z, where we reduced forecasted cash flows from $1 million to $900,000 to account for a possible failure of technology. The project’s PV was reduced from $909,100 to $818,000. You could have gotten the right answer by adding a fudge factor to the discount rate and discounting the original forecast of $1 million. But you have to think through the possible cash flows to get the fudge factor, and once you forecast the cash flows correctly, you don’t need the fudge factor. Fudge factors in discount rates are dangerous because they displace clear thinking about future cash flows. Here is an example. EXAMPLE 9.2 • Correcting for Optimistic Forecasts Torsten Lindstedt, the CFO of Swedish Shipping is disturbed to find that cash-flow forecasts for its investment projects are almost always optimistic.

But later present values are knocked down by much more than 10%, because the fudge factor is compounded in the 22% discount rate. By years 10 and 15, the PV haircuts are 57% and 72%, far more than the 10% bias that the CFO started with. Did the CFO really think that bias accumulated as shown in line 7 of Table 9.2? We doubt that he ever asked that question. If he was right in the first place, and the true bias is 10%, then adding a 10% fudge factor to the discount rate understates PV. The fudge factor also makes long-lived projects look much worse than quick-payback projects.18 Discount Rates for International Projects In this chapter we have concentrated on domestic investments. In Chapter 27 we say more about investments made internationally. Here we simply warn against adding fudge factors to discount rates for projects in developing economies.

What do these analyses reveal about the project’s risks and potential value? ___________ 1There is no First Law. We think “Second Law” sounds better. There is a Third Law, but that is for another chapter. 2Adding a fudge factor to the cost of capital also favors quick-payback projects and penalizes longer-lived projects, which tend to have lower rates of return but higher NPVs. Adding a 5% fudge factor to the discount rate is roughly equivalent to reducing the forecast and present value of the first year’s cash flow by 5%. The impact on the present value of a cash flow 10 years in the future is much greater, because the fudge factor is compounded in the discount rate. The fudge factor is not too much of a burden for a 2- or 3-year project, but an enormous burden for a 10- or 20-year project. 3If you doubt this, try some simple experiments. Ask the person who repairs your dishwasher to state a numerical probability that it will work for at least one more year.


pages: 309 words: 65,118

Ruby by example: concepts and code by Kevin C. Baird

Benevolent Dictator For Life (BDFL), David Heinemeier Hansson, Debian, digital map, Donald Knuth, en.wikipedia.org, Firefox, fudge factor, general-purpose programming language, Guido van Rossum, Larry Wall, MVC pattern, Paul Graham, Perl 6, premature optimization, union organizing, web application

The Unix command wc counts words, but the numbers it reported didn’t necessarily match what a word processor might report; the main reason probably had to do with issues like whether words with fewer than a certain number of letters should count as a “word” in the word processor’s counter. I knew the approximate ratio of the word processor’s 62 C ha pt er 4 word count versus the output of wc (I call this the fudge factor), and I could certainly do the math, but I wanted something that would do all of this for me automatically. Let’s take a look. The Code #!/usr/bin/env ruby # word_count.rb class String def num_matches(thing_to_match) return self.split(thing_to_match).size - 1 end # num_matches end # String BAR_LENGTH = 20 # to match these calculations with the output of some word processors FUDGE_FACTOR = 0.82 def word_count(files) Multiplying Strings output = '' total_word_count = 0 files.each do |filename| file_word_count = word_count_for_file(filename) output += "#{filename} has #{file_word_count} words.

\n" total_word_count += file_word_count end # each file return output + '-' * BAR_LENGTH + "\n" + "Total word count = #{total_word_count}" + " (#{(total_word_count * FUDGE_FACTOR)})" end # word_count def word_count_for_file(filename) f = File.new(filename, 'r') contents = f.read() f.close() spaces = contents.num_matches(' ') breaks = contents.num_matches("\n") false_doubles = contents.num_matches(" \n") double_spaces = contents.num_matches(' ') hyphens = contents.num_matches('-') false_doubles += double_spaces + hyphens words = spaces + breaks - false_doubles + 1 return words end # word_count_for_file puts word_count(ARGV) Te xt M a ni pul at io n 63 How It Works We start out by adding a new method called num_matches to the String class ( ). It simply returns the number of times the argument appears within the calling String. I also define top-level constants called BAR_LENGTH ( ), which is just for visual formatting, and FUDGE_FACTOR ( ), which I already noted is the ratio between the two different word-counting programs I was working with.

The returned expression closes with the total multiplied by the FUDGE_FACTOR constant in parentheses. Before finishing with this script, we need to understand how it calculates the word count for each file. Let’s examine the word_count_for_file function ( ). It opens by getting the contents out of the file being worked on. It then uses some quick-and-dirty calls to the num_matches method on the contents variable to get counts for spaces, line breaks, and so on. It then calculates the number of words in the contents String using those rough numbers. There are more accurate ways to count words in a String, many of which use techniques described in Jeffrey Friedl’s Mastering Regular Expressions. However, this script is intended for quick, approximate results, given that it uses a fudge factor. This script shows that just adding one new method to an existing class can be very handy even for a short, back-of-the-envelope task.


pages: 593 words: 118,995

Relevant Search: With Examples Using Elasticsearch and Solr by Doug Turnbull, John Berryman

commoditize, crowdsourcing, domain-specific language, finite state, fudge factor, full text search, information retrieval, natural language processing, premature optimization, recommendation engine, sentiment analysis

The summation in the preceding dot product can be found in the behavior of the Boolean query that sums up matching clauses. You can see this in sum of from the previous explain: 3.19292, sum of: 3.19292, weight(title:alien in 223) [PerFieldSimilarity] 3.6.3. Practical caveats to the vector space model Although the vector space model provides a general framework for discussing Lucene’s scoring, it’s far from a complete picture. Numerous fudge factors have been shown to improve scoring in practice. Perhaps most fundamentally, the ways matches are combined by compound queries into a larger score isn’t always a summation. You’ve seen through the | symbol that the “max” of two fields is often taken. There’s also often a coord factor that directly punishes compound matches missing some of their components (coord multiplies the resulting dot product by <the number of matches> / <the total query terms>).

You’ll explore many of these strategies in future chapters. Another important note about this dot product is that it’s often normalized by dividing the magnitude of each vector: For dot products, normalization converts the score to a 0–1. This rebalances the equation to account for features that tend to have high weights, and those that tend to have smaller weights.[3] For search, given all the fudge factors in Lucene scoring and the peculiarities of field statistics, you should never attempt to compare scores between queries without a great deal of deep customization to make them comparable. 3 Astute readers will recognize this as the cosine similarity. As stated previously, the sparse vector representation of text is known as the bag of words model. It’s considered a “bag” because it reflects a decomposition of text that ignores the context of these terms.

Taken together, Lucene’s classic similarity measures a term’s weight in a piece of text as follows: TF weighted × IDF weighted × fieldNorm Revisiting the fieldWeight calculation, you see this formula in play: 0.4414702, fieldWeight in 31, product of: 1.4142135, tf(freq=2.0), with freq of: 2.0, termFreq=2.0 3.9957323, idf(docFreq=1, maxDocs=40) 0.078125, fieldNorm(doc=31) Lucene’s next default similarity: BM25 Over the years, an alternate approach to computing a TF × IDF score has become prevalent in the information retrieval community: Okapi BM25. Because of its proven high performance on article-length text, Lucene’s BM25 similarity will be rolling out as the default similarity for Solr/Elasticsearch, even as you read this book. What is BM25? Instead of “fudge factors” as discussed previously, BM25 bases its TF × IDF “fudges” on more-robust information retrieval findings. This includes forcing the impact of TF to reach a saturation point. Instead of the impact of length (fieldNorms) always increasing, its impact is computed relative to the average document length (above-average docs weighted down, below-average boosted). IDF is computed similarly to classic TF × IDF similarity.


pages: 244 words: 68,223

Isaac Newton by James Gleick

Albert Einstein, Astronomia nova, complexity theory, dark matter, Edmond Halley, Fellow of the Royal Society, fudge factor, Isaac Newton, Johannes Kepler, On the Revolutions of the Heavenly Spheres, Richard Feynman, Thomas Kuhn: the structure of scientific revolutions

.… It is necessary to cut loose from such difficulties.” Newton, by contrast, set himself, and science, the obligation to exclude nothing and calculate everything. As Westfall says, “So completely has modern physical science modeled itself on the Principia that we can scarcely realize how unprecedented such calculations were.” It was impossible, given the available data, and sometimes he cheated. Westfall, “Newton and the Fudge Factor,” Science 179 (February 23, 1973): 751. Also Nicholas Kollerstrom, “Newton’s Lunar Mass Error,” Journal of the British Astronomical Association 95 (1995): 151. For another example of what Whiteside calls “the delicate art of numerical cookery,” see Math VI: 508–36. 23. Principia 807. 24. Principia 806. 25. Principia 814. 26. Principia 829. 27. Add MS 3965, “De motu corporum,” in Hall and Hall, Unpublished Scientific Papers, p. 281. 28.

Cambridge, Mass.: Harvard University Press, 2001. Weld, Charles Richard. A History of the Royal Society, with Memoirs of the Presidents. London: 1848. Westfall, Richard S. Force in Newton’s Physics: The Science of Dynamics in the Seventeenth Century. London: Macdonald, 1971. ———. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1980. ———. “Newton and the Fudge Factor,” Science 179: 751. ———. Science and Religion in Seventeenth-Century England. New Haven: Yale University Press, 1958. ———. “Short-Writing and the State of Newton’s Conscience, 1662.” Notes and Records of the Royal Society 18 (1963): 10. Whiston, William. Memoirs of the Life and Writings of Mr. William Whiston. Second edition. London: Whiston & White, 1753. White, Lynn, Jr. Medieval Technology and Social Change.


In the Age of the Smart Machine by Shoshana Zuboff

affirmative action, American ideology, blue-collar work, collective bargaining, computer age, Computer Numeric Control, conceptual framework, data acquisition, demand response, deskilling, factory automation, Ford paid five dollars a day, fudge factor, future of work, industrial robot, information retrieval, interchangeable parts, job automation, lateral thinking, linked data, Marshall McLuhan, means of production, old-boy network, optical character recognition, Panopticon Jeremy Bentham, post-industrial society, RAND corporation, Shoshana Zuboff, social web, The Wealth of Nations by Adam Smith, Thorstein Veblen, union organizing, zero-sum game

I am not sure how much judg- ment you can exercise in using one of these models, but if it has substantiated itself, you just do what it says. An operator who worked regularly with the calculator models de- scribed his frustration at not having access to their underlying assump- tions and algorithms, which he called "fudge factors": 278 AUTHORITY: THE SPIRITUAL DIMENSION OF POWER The models use equations, fudge factors, put in there to make sure you make quality pulp. If you don't know these fudge factors, they can work against you. I had to talk the engineers into explaining the fudge factors to me. The assumptions of the designers are never explained to us. You cannot really be controlling the process if you don't understand these things. As long as it's a black box to me, all I can do is babysit the computer. While this operator had been successful in persuading an engineer to instruct him on some of the more sophisticated issues involved in a model's calculations, most operators had become somewhat embit- tered about the prospects of extracting from their managers the kind of education they needed to really feel empowered at the data interface.


pages: 446 words: 117,660

Arguing With Zombies: Economics, Politics, and the Fight for a Better Future by Paul Krugman

affirmative action, Affordable Care Act / Obamacare, Andrei Shleifer, Asian financial crisis, bank run, banking crisis, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, Bonfire of the Vanities, business cycle, capital asset pricing model, carbon footprint, Carmen Reinhart, central bank independence, centre right, Climategate, cognitive dissonance, cryptocurrency, David Ricardo: comparative advantage, different worldview, Donald Trump, Edward Glaeser, employer provided health coverage, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, frictionless, frictionless market, fudge factor, full employment, Growth in a Time of Debt, hiring and firing, illegal immigration, income inequality, index fund, indoor plumbing, invisible hand, job automation, John Snow's cholera map, Joseph Schumpeter, Kenneth Rogoff, knowledge worker, labor-force participation, large denomination, liquidity trap, London Whale, market bubble, market clearing, market fundamentalism, means of production, New Urbanism, obamacare, oil shock, open borders, Paul Samuelson, plutocrats, Plutocrats, Ponzi scheme, price stability, quantitative easing, road to serfdom, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, secular stagnation, The Chicago School, The Great Moderation, the map is not the territory, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, universal basic income, very high income, working-age population

Their framework, unlike that of the Chicago School, both allows for the possibility of involuntary unemployment and considers it a bad thing. But the New Keynesian models that have come to dominate teaching and research assume that people are perfectly rational and financial markets are perfectly efficient. To get anything like the current slump into their models, New Keynesians are forced to introduce some kind of fudge factor that for reasons unspecified temporarily depresses private spending. (I’ve done exactly that in some of my own work.) And if the analysis of where we are now rests on this fudge factor, how much confidence can we have in the models’ predictions about where we are going? The state of macro, in short, is not good. So where does the profession go from here? VII. FLAWS AND FRICTIONS Economics, as a field, got in trouble because economists were seduced by the vision of a perfect, frictionless market system.


UNIX® Network Programming, Volume 1: The Sockets Networking API, 3rd Edition by W. Richard Stevens, Bill Fenner, Andrew M. Rudoff

failed state, fudge factor, information retrieval, p-value, RFC: Request For Comment, Richard Stallman, web application

The historical definition in this bullet is the Berkeley implementation, dating back to 4.2BSD, and copied by many others. • Berkeley-derived implementations add a fudge factor to the backlog: It is multiplied by 1.5 (p. 257 of TCPv1 and p. 462 of TCPv2). For example, the commonly specified backlog of 5 really allows up to 8 queued entries on these systems, as we show in Figure 4.10. The reason for adding this fudge factor appears lost to history [Joy 1994]. But if we consider the backlog as specifying the maximum number of completed connections that the kernel will queue for a socket ([Borman 1997b], as discussed shortly), then the reason for the fudge factor is to take into account incomplete connections on the queue. • Do not specify a backlog of 0, as different implementations interpret this differently (Figure 4.10).

Space is then allocated for the buffer and sysctl is called again, this time with a non-null third argument. This time, the variable pointed to by lenp will return with the amount of information stored in the buffer, and this variable is allocated by the caller. A pointer to the buffer is also returned to the caller. Since the size of the routing table or the number of interfaces can change between the two calls to sysctl, the value returned by the first call contains a 10% fudge factor (pp. 639 – 640 of TCPv2). Section 18.5 get_ifi_info Function (Revisited) 501 Figure 18.16 shows the first half of the get_ifi_info function. 3 struct ifi_info * 4 get_ifi_info(int family, int doaliases) 5 { 6 int flags; 7 char *buf, *next, *lim; 8 size_t len; 9 struct if_msghdr *ifm; 10 struct ifa_msghdr *ifam; 11 struct sockaddr *sa, *rti_info[RTAX_MAX]; 12 struct sockaddr_dl *sdl; 13 struct ifi_info *ifi, *ifisave, *ifihead, **ifipnext; route/get_ifi_info.c 14 buf = Net_rt_iflist(family, 0, &len); 15 16 ifihead = NULL; ifipnext = &ifihead; 17 18 19 20 21 22 lim = buf + len; for (next = buf; next < lim; next += ifm->ifm_msglen) { ifm = (struct if_msghdr *) next; if (ifm->ifm_type == RTM_IFINFO) { if (((flags = ifm->ifm_flags) & IFF_UP) == 0) continue; /* ignore if interface not up */ 23 24 25 26 27 28 sa = (struct sockaddr *) (ifm + 1); get_rtaddrs(ifm->ifm_addrs, sa, rti_info); if ( (sa = rti_info[RTAX_IFP]) !

., xxiii free function, 508, 684 free_ifi_info function, 471, 478 source code, 480 freeaddrinfo function, 321, 327, 345 definition of, 321 FreeBSD, 20 – 24, 78, 108, 197, 260 – 262, 299, 405, 469, 473, 497, 538, 658, 666, 710, 775, 882 – 883, 891, 897, 904, 926, 934, 939 – 940 freehostent function, 347 definition of, 347 frequently asked question, see FAQ fseek function, 400 fsetpos function, 400 fstat function, 406 fstat program, 897 FTP (File Transfer Protocol), 20, 62, 201, 311 – 312, 360, 362, 366, 375, 662, 914, 947 fudge factor, 106, 500 full-duplex, 36, 415 Fuller, V., 874, 949 fully buffered standard I/O stream, 401 fully qualified domain name, see FQDN function destructor, 690 system call versus, 891 wrapper, 11 – 13 gai_strerror function, 320 – 321 definition of, 321 Ganguly, S., 285, 953 Garcia, M., 267, 952 Garfinkel, S. L., 15, 949 gated program, 199, 485, 735 gather write, 389 Gemellaro, A., xxiii generic socket address structure, 70 – 71 new, 72 – 73 get_ifi_info function, 469 – 480, 482, 484, 500 – 503, 582, 608 source code, 474, 501 get_rtaddrs function, 492 – 493, 502, 505 getaddrinfo function, 10, 15, 38, 93, 232, 303, 307, 315 – 329, 332 – 336, 338, 340 – 341, 343, 345 – 347, 349, 357, 361, 620, 746, 932, 941 definition of, 315 examples, 324 – 325 IPv6, 322 – 323 getc_unlocked function, 685 getchar_unlocked function, 685 Index 963 getconninfo function, 315 getgrid function, 685 getgrid_r function, 685 getgrnam function, 685 getgrnam_r function, 685 gethostbyaddr function, 303, 305 – 306, 310, 315, 341 – 343, 346, 348 – 350, 361, 685, 928 – 930 definition of, 310 gethostbyaddr_r function, 344 – 346 definition of, 345 gethostbyname function, 303, 305 – 310, 312, 314 – 315, 320, 329, 341 – 350, 355, 361, 685, 929 – 930, 932 – 933 definition of, 307 gethostbyname2 function, 342, 346 – 347 definition of, 347 gethostbyname_r function, 344 – 346 definition of, 345 gethostent function, 349 getifaddrs function, 469 getipnodebyaddr function, 347 getipnodebyname function, 347 definition of, 347 getlogin function, 685 getlogin_r function, 685 getmsg function, 155, 809 – 810, 855 – 857, 860, 862, 864 – 868, 891 definition of, 856 getnameinfo function, 38, 93, 303, 320, 331, 340 – 341, 343, 345, 347, 349 – 350, 361, 762, 933 definition of, 340 getnameinfo_timeo function, 350 getnetbyaddr function, 348 getnetbyname function, 348 getopt function, 516, 796 getpeername function, 52, 68, 75, 117 – 120, 147, 275, 329, 340, 377 – 378, 451 definition of, 118 getpid function, 678 getpmsg function, 855, 857, 868 definition of, 857 getppid function, 111, 938 getprotobyname function, 348 getprotobynumber function, 348 getpwnam function, 373, 685 getpwnam_r function, 685 getpwuid function, 685 getpwuid_r function, 685 getrlimit function, 919 getrusage function, 824, 827 gets function, 15 getsatypebyname function, 516 getservbyaddr function, 348 getservbyname function, 303, 311 – 314, 320, 329, 343, 348 – 349, 373 definition of, 311 964 UNIX Network Programming getservbyport function, 303, 311 – 314, 343, 348 definition of, 312 getsockname function, 68, 75, 103, 117 – 120, 146 – 147, 211, 230, 251, 261, 340, 413 – 414, 769, 779, 915, 932 definition of, 118 getsockopt function, 76, 165, 191 – 194, 197, 200, 215, 218, 222 – 223, 226, 230, 237, 278, 451, 459, 559, 617, 710, 714, 717 – 718, 733, 740 definition of, 192 gettimeofday function, 582, 606, 704 – 705, 747 Gettys, J., 294, 949 getuid function, 799 gf_time function, 442 source code, 442 Gierth, A., 462, 949 GIF (graphics interchange format), 454, 825 Gilliam, W., xxiii Gilligan, R.


pages: 124 words: 40,697

The Grand Design by Stephen Hawking, Leonard Mlodinow

airport security, Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Buckminster Fuller, conceptual framework, cosmic microwave background, cosmological constant, dark matter, fudge factor, invention of the telescope, Isaac Newton, Johannes Kepler, John Conway, John von Neumann, luminiferous ether, Mercator projection, Richard Feynman, Stephen Hawking, Thales of Miletus, the scientific method, Turing machine

This is probably apocryphal, but we do know he rolled different weights down an inclined plane and observed that they all gathered speed at the same rate, contrary to Aristotle’s prediction. The above criteria are obviously subjective. Elegance, for example, is not something easily measured, but it is highly prized among scientists because laws of nature are meant to economically compress a number of particular cases into one simple formula. Elegance refers to the form of a theory, but it is closely related to a lack of adjustable elements, since a theory jammed with fudge factors is not very elegant. To paraphrase Einstein, a theory should be as simple as possible, but not simpler. Ptolemy added epicycles to the circular orbits of the heavenly bodies in order that his model might accurately describe their motion. The model could have been made more accurate by adding epicycles to the epicycles, or even epicycles to those. Though added complexity could make the model more accurate, scientists view a model that is contorted to match a specific set of observations as unsatisfying, more of a catalog of data than a theory likely to embody any useful principle.


pages: 420 words: 124,202

The Most Powerful Idea in the World: A Story of Steam, Industry, and Invention by William Rosen

"Robert Solow", Albert Einstein, All science is either physics or stamp collecting, barriers to entry, collective bargaining, computer age, Copley Medal, creative destruction, David Ricardo: comparative advantage, decarbonisation, delayed gratification, Fellow of the Royal Society, Flynn Effect, fudge factor, full employment, invisible hand, Isaac Newton, Islamic Golden Age, iterative process, James Hargreaves, James Watt: steam engine, John Harrison: Longitude, Joseph Schumpeter, Joseph-Marie Jacquard, knowledge economy, moral hazard, Network effects, Panopticon Jeremy Bentham, Paul Samuelson, Peace of Westphalia, Peter Singer: altruism, QWERTY keyboard, Ralph Waldo Emerson, rent-seeking, Ronald Coase, Simon Kuznets, spinning jenny, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, transcontinental railway, zero-sum game, éminence grise

It isn’t, of course, that Britain didn’t have its own Réaumurs—the Royal Society was full of skilled scientists uninterested in any involvement in commerce—but rather that it also had thousands of men like Darby: an inventor and engineer who cared little about scientific glory but a whole lot about pots and pans. IF THE CAST IRON used for pots and pans was the most mundane version of the element, the most sublime was steel. As with all iron alloys, carbon is steel’s critical component. In its simplest terms, wrought iron has essentially no minimum amount of carbon, just as there is no maximum carbon content for cast iron. As a result, the recipe for either has a substantial fudge factor. Not so with steel. Achieving steel’s unique combination of strengths demands a very narrow range of carbon: between 0.25 percent and a bit less than 2 percent. For centuries* this has meant figuring out how to initiate the process whereby carbon insinuates itself into iron’s crystalline structure, and how to stop it once it achieves the proper percentage. The techniques used have ranged from the monsoon-driven wind furnaces of south Asia to the quenching and requenching of white-hot iron in water, all of which made steelmaking a boutique business for centuries: good for swords and other edged objects, but not easy to scale up for the production of either a few large pieces or many smaller ones.

Except during times of dramatic depopulation, such as the Black Death of the fourteenth century, or extremely large additions to the stock of arable land, as with Europe’s discovery of the New World, growth in land per worker has been negligible for centuries, so small that its effect on growth can be eliminated in the simplest calculations. The second component, growth in capital3 per worker—that is, all the buildings, machinery, tools, and so on—explains only about 24 percent of total growth. However, since the growth in the amount of land and capital per worker together doesn’t equal the overall growth rate, a fudge factor must be used, called the residual: what’s left over. This also means that the residual, despite the ass-backward way it is calculated, amounts to at least three-quarters of the total increase in economic growth since 1800. That’s a big chunk of activity defined by subtracting everything else, a little like a ten-drawer file cabinet with seven drawers marked “Miscellaneous.” Solow first assumed4 that the residual represented increasing efficiency over time, and he incorporated an arbitrary constant to represent the rate of the growth in useful knowledge.


pages: 226 words: 59,080

Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik

airline deregulation, Albert Einstein, bank run, barriers to entry, Bretton Woods, business cycle, butterfly effect, capital controls, Carmen Reinhart, central bank independence, collective bargaining, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, distributed generation, Donald Davies, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, Fellow of the Royal Society, financial deregulation, financial innovation, floating exchange rates, fudge factor, full employment, George Akerlof, Gini coefficient, Growth in a Time of Debt, income inequality, inflation targeting, informal economy, information asymmetry, invisible hand, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, labor-force participation, liquidity trap, loss aversion, low skilled workers, market design, market fundamentalism, minimum wage unemployment, oil shock, open economy, Pareto efficiency, Paul Samuelson, price stability, prisoner's dilemma, profit maximization, quantitative easing, randomized controlled trial, rent control, rent-seeking, Richard Thaler, risk/return, Robert Shiller, Robert Shiller, school vouchers, South Sea Bubble, spectrum auction, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, trade liberalization, trade route, ultimatum game, University of East Anglia, unorthodox policies, Vilfredo Pareto, Washington Consensus, white flight

But ask them whether the model is more relevant to Bolivia or to Thailand, or whether it resembles more the market for cable TV or the market for oranges, and they will have a hard time producing an articulate answer. The standards of the profession require that the modeler make only some general claims about how what he or she is doing is relevant to the real world. It is left to the reader or the user of the model to infer the specific circumstances in which the model can help us better understand reality.§ This fudge factor increases the chances of malpractice. Models lifted out of their original context can be used in settings for which they are inappropriate. At the empirical end of economics, such as labor and development economics, where almost all economists work directly with data and real-world evidence, paradoxically the problems may be even more severe. This is because the underlying model is often left unspecified from the outset.


They Have a Word for It A Lighthearted Lexicon of Untranslatable Words & Phrases-Sarabande Books (2000) by Howard Rheingold

Ayatollah Khomeini, clockwork universe, fudge factor, Howard Rheingold, informal economy, Kula ring, Lao Tzu, Ronald Reagan, Rosa Parks, Silicon Valley, the map is not the territory, the scientific method

The Germans named this odious type, but there's no reason why their contemptuous word shouldn't be more widely adopted. /aux.frais(French) Items you are likely to forget to include when making a budget. [noun] Here's a problem that vexes small households and sovereign nations: figuring out in advance how you are going to spend your money. No matter how thoroughly you do your research, how conscientiously you build in fudge factors, Serious Business 127 how hard you work at sticking to a prearranged budget, doesn't it seem as if you always end up outspending your target amount, especially if it is an annual budget? How does this happen? Did you remember to include the cost of replacing a cracked windshield or removing an impacted wisdom tooth? Life is an illusory raft on an ocean of uncertain ties. How can you ever anticipate all the expenses that can possibly pop up in the course of a year?


pages: 231 words: 71,248

Shipping Greatness by Chris Vander Mey

corporate raider, don't be evil, en.wikipedia.org, fudge factor, Google Chrome, Google Hangouts, Gordon Gekko, Jeff Bezos, Kickstarter, Lean Startup, minimum viable product, performance metric, recommendation engine, Skype, slashdot, sorting algorithm, source of truth, Steve Jobs, Superbowl ad, web application

., for each three days of development, you need one day of your test team to test). The testing constant is a function of the size of your test team. In the spreadsheet shown in Figure 4-1, I’ve added some calculations to ensure that tasks don’t end on the weekends. Because this model uses “ideal” developer days for estimates, it is critical to build a buffer into your dates, but not the engineering task estimates. A buffer is a “fudge factor” that accommodates unforeseen problems and general productivity losses. Some teams estimate that approximately three out of five days are productive. Anything could be happening in those two days, but it’s likely some combination of meetings, broken builds, marriage problems, and false starts. It’s pretty hard to eliminate those distractions, and as a result I find that 60% productivity is a good estimate.


pages: 265 words: 74,807

Our Robots, Ourselves: Robotics and the Myths of Autonomy by David A. Mindell

Air France Flight 447, autonomous vehicles, Captain Sullenberger Hudson, Charles Lindbergh, Chris Urmson, digital map, disruptive innovation, drone strike, en.wikipedia.org, Erik Brynjolfsson, fudge factor, index card, John Markoff, low earth orbit, Mars Rover, ride hailing / ride sharing, Ronald Reagan, self-driving car, Silicon Valley, telepresence, telerobotics, trade route, US Airways Flight 1549, William Langewiesche, zero-sum game

By one engineer estimating the difference between stopped and moving and dialing it in to the algorithm. I asked my colleague Jon How, one of the principals on the project, how many such thresholds there are in a system like that. His reply: “Many, many, many.” In fact the “configuration file” for the MIT vehicle contained nearly a thousand lines of text, setting hundreds of variables: sensor positions and calibrations, fudge factors to align the sensors with one another, how to deal with sun dazzle, etc. Machine learning techniques can help reduce this reliance on parameters, but they still rely on human programmers for their basic structure. How points out that core algorithms generally rely heavily on accurate models of uncertainty in the world. As he observes, “The problem of autonomy is fundamentally the problem of living in an uncertain world.”


pages: 294 words: 85,811

The Healing of America: A Global Quest for Better, Cheaper, and Fairer Health Care by T. R. Reid

Berlin Wall, British Empire, double helix, employer provided health coverage, fudge factor, Kenneth Arrow, medical malpractice, profit maximization, profit motive, single-payer health, South China Sea, the payments system

In terms of “Fairness of financial contribution,” the United States was rated fifty-fourth. Colombia, with health care funded by a steeply progressive tax code, topped the chart on this scale, followed closely by western European countries and Japan. Finally, the WHO experts took all these factors, tabulated each country’s score on each measure, and arrived at its rating of “overall performance.” But this score was adjusted by one more fudge factor: a comparison of each country’s actual performance on national health care to the overall performance it should have been able to achieve, considering its level of education and the amount of money it spends on health care.With this ultimate wrinkle factored in, the report finally came up with its ranking of “overall performance” in all 191 member nations. When the figures were all computed, the French health care system was rated first in the world—and the United States, thirty-seventh.


pages: 345 words: 86,394

Frequently Asked Questions in Quantitative Finance by Paul Wilmott

Albert Einstein, asset allocation, beat the dealer, Black-Scholes formula, Brownian motion, butterfly effect, buy and hold, capital asset pricing model, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, discrete time, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, iterative process, lateral thinking, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, martingale, Myron Scholes, Norbert Wiener, Paul Samuelson, quantitative trading / quantitative finance, random walk, regulatory arbitrage, risk/return, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, stochastic volatility, transaction costs, urban planning, value at risk, volatility arbitrage, volatility smile, Wiener process, yield curve, zero-coupon bond

First, if we do start to move outside the Black-Scholes world then chances are it will be the diffusion coefficient that we must change from its usual to accommodate new models. Second, if we want to fudge our option prices, to massage them into line with traded prices for example, we can only do so by fiddling with this diffusion coefficient, i.e. what we now know to be the volatility. This derivation tells us that our only valid fudge factor is the volatility. Black-Scholes for Accountants The final derivation of the Black-Scholes equation requires very little complicated mathematics, and doesn’t even need assumptions about Gaussian returns, all we need is for the variance of returns to be finite. The Black-Scholes analysis requires continuous hedging, which is possible in theory but impossible, and even undesirable, in practice.


pages: 266 words: 78,986

Quarantine by Greg Egan

cosmic microwave background, dark matter, fudge factor, intermodal, pattern recognition, placebo effect, Schrödinger's Cat

I’m just sick of being bullied, and patronized, and gagged. That’s all.’ ‘What’s Leung done now?’ ‘Oh, nobody’s done anything. Nothing’s changed. It just… all seems even more stupid and oppressive than usual, today. I read an article in Physical Review this morning: a whole new treatment of the measurement problem. They add a few more dimensions to space-time; throw in a few nonlinearities, asymmetries and assorted fudge factors; and—miracle of miracles!—the collapse of the wave falls out the other end.’ I know I should have dutifully silenced her half-way through the word ‘measurement’—if only for the sake of appearances—but the hypocrisy would have been too much. She says, ‘People are wasting valuable time, heading down paths that I know are blind alleys. That makes me a liar by default. I don’t expect Leung to divulge any commercial secrets—like neural maps, or details of the mod—but I don’t see why we can’t at least publish the results of the experiments.’


pages: 340 words: 91,745

Duped: Double Lives, False Identities, and the Con Man I Almost Married by Abby Ellin

Bernie Madoff, bitcoin, Burning Man, business intelligence, Charles Lindbergh, cognitive dissonance, Donald Trump, double helix, dumpster diving, East Village, feminist movement, forensic accounting, fudge factor, hiring and firing, Internet Archive, longitudinal study, Lyft, mandatory minimum, meta analysis, meta-analysis, pink-collar, Ponzi scheme, Robert Hanssen: Double agent, Ronald Reagan, Silicon Valley, Skype, Snapchat, telemarketer, theory of mind, Thomas Kuhn: the structure of scientific revolutions

They wanted to turn themselves into a reasonably better specimen, but not make it seem like they were, um, lying. What if they claimed to be six feet tall but were a mere five foot three in real life? People would notice that kind of discrepancy. But if they said they were five four and were really five three? That was a little more plausible. What’s an inch among lovers?3 Behavioral economist Dan Ariely, author of The (Honest) Truth About Dishonesty, said we all cheat by a “fudge factor” of roughly 15 percent.4 But some of us advance to such big lies that we’re practically drowning in the gooey concoction. The Commander certainly used fragments of the truth, combined them with untruths, and shot it all out of a cannon. He really was a doctor in private practice in Beverly Hills, and had a PhD and an MD. He did have an ex-wife and two kids, and his mother really had been a radio actress in the 1930s.


pages: 269 words: 104,430

Carjacked: The Culture of the Automobile and Its Effect on Our Lives by Catherine Lutz, Anne Lutz Fernandez

barriers to entry, car-free, carbon footprint, collateralized debt obligation, failed state, feminist movement, fudge factor, Gordon Gekko, housing crisis, illegal immigration, income inequality, inventory management, market design, market fundamentalism, mortgage tax deduction, Naomi Klein, Nate Silver, New Urbanism, oil shock, peak oil, Ralph Nader, Ralph Waldo Emerson, ride hailing / ride sharing, Thorstein Veblen, traffic fines, Unsafe at Any Speed, urban planning, white flight, women in the workforce, working poor, Zipcar

With greater model diversity and the niche marketing of those models to a complex set of demographics that began most vigorously in the 1970s, the automobile became more than a marker of class.21 And in an environment where credit is sold so aggressively, the car today is less a reliable sign of hard work done and money earned than of hard work yet to be done and money yet to be earned. (Now the more appropriate comment to a new car buyer might be “Congratulations on your debt!”) Despite these fudging factors, class remains legible in one’s car, a fact that provides some of the sweetest pleasures to those who drive more expensive and late-model cars. Even the way some talk about how they drive sounds a lot like how they think about getting ahead. Said one man: “I have a life philosophy. If you do what the herd does, you get what the herd gets.” So when he sees packs of cars moving together, he said, he zooms up to them, gets through and barrels away as fast as possible.


pages: 383 words: 108,266

Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions by Dan Ariely

air freight, Al Roth, Bernie Madoff, Burning Man, butterfly effect, Cass Sunstein, collateralized debt obligation, computer vision, corporate governance, credit crunch, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, endowment effect, financial innovation, fudge factor, Gordon Gekko, greed is good, housing crisis, IKEA effect, invisible hand, lake wobegon effect, late fees, loss aversion, market bubble, Murray Gell-Mann, payday loans, placebo effect, price anchoring, Richard Thaler, second-price auction, Silicon Valley, Skype, The Wealth of Nations by Adam Smith, Upton Sinclair

On one hand, we want to look in the mirror and feel good about ourselves (ergo, “I can’t even look at myself in the mirror” is an indicator of one’s own guilt). On the other hand, we’re selfish, and we want to benefit from cheating. On the surface, these two motivations seem contradictory, but our flexible psychology allows us to act on both of them when we cheat “just by a bit”—benefiting financially from cheating while at the same time managing not to feel bad about ourselves. I think of this as an individual “fudge factor,” or a fuzzy conscience. One way to look at the experiments described in Chapters 11 and 12 is to think about them as an examination of what happens when people wrestle with conflicting interests. When we placed participants in situations in which they were torn between wanting to behave honorably and wanting to benefit financially, they usually succumbed to temptation but only by a little bit.


pages: 407 words: 116,726

Infinite Powers: How Calculus Reveals the Secrets of the Universe by Steven Strogatz

Albert Einstein, Asperger Syndrome, Astronomia nova, Bernie Sanders, clockwork universe, complexity theory, cosmological principle, Dava Sobel, double helix, Edmond Halley, Eratosthenes, four colour theorem, fudge factor, Henri Poincaré, invention of the telescope, Isaac Newton, Islamic Golden Age, Johannes Kepler, John Harrison: Longitude, Khan Academy, Laplace demon, lone genius, music of the spheres, pattern recognition, Paul Erdős, Pierre-Simon Laplace, precision agriculture, retrograde motion, Richard Feynman, Socratic dialogue, Solar eclipse in 1919, Steve Jobs, the rule of 72, the scientific method

This conclusion was hard to accept at the time. No one could imagine a universe so immense with stars so remote, much farther away than the planets. Today we know that is exactly the case, but back then it was inconceivable. So the Earth-centered cosmology, for all its faults, seemed like the more plausible picture. Suitably modified by the ancient Greek astronomer Ptolemy with epicycles, equants, and other fudge factors, the theory could be made to account reasonably well for planetary motion and it kept the calendar in line with seasonal cycles. The Ptolemaic system was clunky and complicated, but it worked well enough to last into the late Middle Ages. Two books published in 1543 marked a turning point, the beginning of the scientific revolution. In that year, the Flemish doctor Andreas Vesalius reported the results of his dissections of human cadavers, a practice that had been forbidden in earlier centuries.


pages: 426 words: 115,150

Your Money or Your Life: 9 Steps to Transforming Your Relationship With Money and Achieving Financial Independence: Revised and Updated for the 21st Century by Vicki Robin, Joe Dominguez, Monique Tilford

asset allocation, Buckminster Fuller, buy low sell high, credit crunch, disintermediation, diversification, diversified portfolio, fiat currency, financial independence, fixed income, fudge factor, full employment, Gordon Gekko, high net worth, index card, index fund, job satisfaction, Menlo Park, money market fund, Parkinson's law, passive income, passive investing, profit motive, Ralph Waldo Emerson, Richard Bolles, risk tolerance, Ronald Reagan, Silicon Valley, software patent, strikebreaker, Thorstein Veblen, Vanguard fund, zero-coupon bond

We might search our souls and discuss with our mate the advisability of spending $40 for a new four-color left-handed veeblefitzer, yet over the course of a month an even larger amount has unconsciously gone out of our universe in small “insignificant” purchases (the “nickel and diming yourself to death” syndrome). “But must I keep track of every cent?” you may ask. Yes, every cent! Why every cent, rather than just rounding off to the nearest dollar, or using approximate figures? Because this helps to establish important lifelong habits. After all, how big is a “Finagler’s Constant”? What’s the definition of a “Fudge Factor”? How close is “close enough”? Granted, in practice many FIers settle into rounding to the dollar, but that’s as far as they slip. Human nature being what it is, if you start cheating, even “just a little bit,” that little bit tends to get bigger and soon you’ll find yourself thinking, “Well, I don’t have to write everything down, just the major expenses”; and then, “Well, I’ve done this for a month now, so I think I’ll start rounding it off to the nearest thousand.”


pages: 431 words: 118,074

The Ultimate Engineer: The Remarkable Life of NASA's Visionary Leader George M. Low by Richard Jurek

additive manufacturing, affirmative action, Charles Lindbergh, cognitive dissonance, en.wikipedia.org, fudge factor, John Conway, low earth orbit, Mars Rover, operation paperclip, orbital mechanics / astrodynamics, Ronald Reagan, Silicon Valley, Silicon Valley ideology, Stewart Brand, undersea cable, uranium enrichment, Whole Earth Catalog, Winter of Discontent, women in the workforce

“I was particularly concerned that we might be selling it at too low a cost and would forever be defending cost increases. I mentioned that one of the things that made Apollo feasible was Jim Webb’s original estimate of between $20 to $40 billion,” he explained. Apollo came in at around $24 billion; in his original Low committee report, he had estimated the program at just $7 billion. Webb, an old budget hand, knew the game of government budgets. He multiplied Low’s estimate by a healthy fudge factor. It worked. “With Webb’s high estimate, we never had a problem in defending Apollo costs again during the early days of the program,” he explained to Paine.16 “The agency’s initial budget request in 1970 started out at $4.5 billion for 1971. It was based on moving out with speed on the Space Task Group’s planning,” Low remembered. “About the time I came in, we got one budget after another, and we had meeting after meeting, and each time, we came back with a little bit less money than before.”17 In the end, NASA’s budget got slashed by a third, coming in at just a little over $3 billion.


pages: 412 words: 122,952

Day We Found the Universe by Marcia Bartusiak

Albert Einstein, Albert Michelson, Arthur Eddington, California gold rush, Cepheid variable, Copley Medal, cosmic microwave background, cosmological constant, Edmond Halley, Edward Charles Pickering, Fellow of the Royal Society, fudge factor, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, horn antenna, invention of the telescope, Isaac Newton, Louis Pasteur, Magellanic Cloud, Occam's razor, orbital mechanics / astrodynamics, Pluto: dwarf planet, Solar eclipse in 1919, William of Occam

Even Newton knew that matter distributed throughout a finite space would eventually coalesce into larger and larger lumps. Stellar objects would be gravitationally drawn to one another, closer and closer over time. Ultimately, the universe would collapse under the inescapable pull of gravity. So, to avoid this cosmic calamity and match his theory with then-accepted astronomical observations, Einstein altered his famous equation, adding the term λ (the Greek letter lambda), a fudge factor that came to be called the “cosmological constant.” This new ingredient was an added energy that permeated empty space and exerted an outward “pressure” on it. This repulsive field—a kind of antigravity, actually—exactly balanced the inward gravitational attraction of all the matter in his closed universe, keeping it from moving. As a result, the universe remained immobile, “as required by the fact of the small velocities of the stars,” wrote Einstein in his classic 1917 paper.


pages: 1,197 words: 304,245

The Invention of Science: A New History of the Scientific Revolution by David Wootton

agricultural Revolution, Albert Einstein, British Empire, clockwork universe, Commentariolus, commoditize, conceptual framework, Dava Sobel, double entry bookkeeping, double helix, en.wikipedia.org, Ernest Rutherford, Fellow of the Royal Society, fudge factor, germ theory of disease, Google X / Alphabet X, Hans Lippershey, interchangeable parts, invention of gunpowder, invention of the steam engine, invention of the telescope, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Johannes Kepler, John Harrison: Longitude, knowledge economy, lateral thinking, lone genius, Mercator projection, On the Revolutions of the Heavenly Spheres, Philip Mirowski, placebo effect, QWERTY keyboard, Republic of Letters, social intelligence, spice trade, spinning jenny, the scientific method, Thomas Kuhn: the structure of scientific revolutions

In From Natural Philosophy to the Sciences: Writing the History of Nineteenth-century Science. Ed. D Cahan. Chicago: University of Chicago Press, 2003: 221–53. Wesley, Walter G. ‘The Accuracy of Tycho Brahe’s Instruments’. Journal for the History of Astronomy 9 (1978): 42–53. Westfall, Richard S. ‘The Development of Newton’s Theory of Color’. Isis (1962): 339–58. ———. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1980. ———. ‘Newton and the Fudge Factor’. Science 179 (1973): 751–8. ———. ‘Science and Technology during the Scientific Revolution: An Empirical Approach’. In Renaissance and Revolution. Humanists, Scholars, Craftsmen and Natural Philosophers in Early Modern Europe. Ed. JV Field and FA James. Cambridge: Cambridge University Press, 1997: 63–72. ———. ‘The Scientific Revolution Reasserted’. In Rethinking the Scientific Revolution. Ed.

Bacon, The Advancement of Learning (1605), 31; and Brown, ‘The Evolution of the Term “Mixed Mathematics”’ (1991). 47. Galileo’s second letter on sunspots (1612), in Galilei & Scheiner, On Sunspots (2008), 107–70. 48. ‘Préface sur le traité du vuide’, in Pascal, Oeuvres complètes (1964), Vol. 2, 772–85. 49. Dear, Discipline and Experience (1995), 15, 180; for an example published by Riccioli in 1651, 78. 50. Palmerino, ‘Experiments, Mathematics, Physical Causes’ (2010); and Westfall, ‘Newton and the Fudge Factor’ (1973). 51. The legal issues and their history were recently summarized in the House of Lords judgement on Regina v. Pendleton, 13 Dec. 2001. 52. Locke, An Essay (1690), 333. 53. Hobbes, Humane Nature (1650), 38–9; quoted in Hacking, The Emergence of Probability (2006), 48 54. Wotton, Reflections upon Ancient and Modern Learning (1694), 301. 55. Seneca, Seneca’s Morals Abstracted (1679), Part 3, 99–100. 56.


pages: 478 words: 131,657

Tesla: Man Out of Time by Margaret Cheney

Charles Lindbergh, dematerialisation, fudge factor, invention of radio, luminiferous ether, Menlo Park

The new physics boiled with debates over waves versus particles and about Einstein’s special theory of relativity, which Tesla—with strong cosmic theories of his own—rejected outright. When Einstein’s general theory of relativity was published in 1916, even its creator had been unable to accept fully the dynamic universe that it implied. So disturbed was Einstein by this that he built into his calculations a “fudge factor” that preserved the possibility that the universe might after all prove to be stable and unchanging. To Tesla this was just added proof that the relativists didn’t know what they were talking about. He himself was working on a theory of the universe to be disclosed in good time, and he had long ago propounded (but not published) his own dynamic theory of gravity. He believed and had often stated, that atomic power would be 1. a dud, or 2. impossibly dangerous to control.


pages: 532 words: 133,143

To Explain the World: The Discovery of Modern Science by Steven Weinberg

Albert Einstein, Alfred Russel Wallace, Astronomia nova, Brownian motion, Commentariolus, cosmological constant, dark matter, Dava Sobel, double helix, Edmond Halley, Eratosthenes, Ernest Rutherford, fudge factor, invention of movable type, Isaac Newton, James Watt: steam engine, Johannes Kepler, music of the spheres, On the Revolutions of the Heavenly Spheres, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, retrograde motion, Thomas Kuhn: the structure of scientific revolutions

Crease, World in the Balance—The Historic Quest for an Absolute System of Measurement (W. W. Norton, New York, 2011). 13. See J. Z. Buchwald and M. Feingold, Newton and the Origin of Civilization (Princeton University Press, Princeton, N.J., 2014). 14. See S. Chandrasekhar, Newton’s Principia for the Common Reader (Clarendon, Oxford, 1995), pp. 472–76; Westfall, Never at Rest, pp. 736–39. 15. R. S. Westfall, “Newton and the Fudge Factor,” Science 179, 751 (1973). 16. See G. E. Smith, “How Newton’s Principia Changed Physics,” in Interpreting Newton: Critical Essays, ed. A. Janiak and E. Schliesser (Cambridge University Press, Cambridge, 2012), pp. 360–95. 17. Voltaire, Philosophical Letters, trans. E. Dilworth (Bobbs-Merrill Educational Publishing, Indianapolis, Ind., 1961), p. 61. 18. The opposition to Newtonianism is described in articles by A.


pages: 692 words: 127,032

Fool Me Twice: Fighting the Assault on Science in America by Shawn Lawrence Otto

affirmative action, Albert Einstein, anthropic principle, Berlin Wall, Brownian motion, carbon footprint, Cepheid variable, clean water, Climategate, Climatic Research Unit, cognitive dissonance, Columbine, commoditize, cosmological constant, crowdsourcing, cuban missile crisis, Dean Kamen, desegregation, different worldview, double helix, energy security, Exxon Valdez, fudge factor, ghettoisation, global pandemic, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Louis Pasteur, mutually assured destruction, Richard Feynman, Ronald Reagan, Saturday Night Live, shareholder value, sharing economy, smart grid, Solar eclipse in 1919, stem cell, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, University of East Anglia, War on Poverty, white flight, Winter of Discontent, working poor, yellow journalism, zero-sum game

In fact, Einstein himself had originally calculated that the universe was expanding, but he was a theoretician, not an astronomer. When he turned to astronomers for verification of his theory, he found that almost all of them held the notion that the universe existed in a steady state and there was no motion on a grand scale. So in deference to their observational experience, Einstein adjusted his general theory calculations with a mathematical “fudge factor”—the cosmological constant—that made the universe seem to be steady. Lemaître had independently been working off the same mathematical principles that Einstein had originally laid out, and in 1927 he wrote a dissenting paper in which he argued that the universe must be expanding, and that if it was, the redshifted light from stars was the result of this expansion. This redshift had been observed by a number of astronomers, but until then there had been no consensus on what the cause could be.


pages: 696 words: 143,736

The Age of Spiritual Machines: When Computers Exceed Human Intelligence by Ray Kurzweil

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Buckminster Fuller, call centre, cellular automata, combinatorial explosion, complexity theory, computer age, computer vision, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, first square of the chessboard / second half of the chessboard, fudge factor, George Gilder, Gödel, Escher, Bach, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, social intelligence, speech recognition, Steven Pinker, Stewart Brand, stochastic process, technological singularity, Ted Kaczynski, telepresence, the medium is the message, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, Y2K

THE END OF THE UNIVERSE What does the Law of Time and Chaos say about the end of the Universe? One theory is that the Universe will continue its expansion forever. Alternatively, if there’s enough stuff, then the force of the Universe’s own gravity will stop the expansion, resulting in a final “big crunch.” Unless, of course, there’s an antigravity force. Or if the “cosmological constant,” Einstein’s “fudge factor,” is big enough. I’ve had to rewrite this paragraph three times over the past several months because the physicists can’t make up their minds. The latest speculation apparently favors indefinite expansion. Personally, I prefer the idea of the Universe closing in again on itself as more aesthetically pleasing. That would mean that the Universe would reverse its expansion and reach a singularity again.


pages: 492 words: 149,259

Big Bang by Simon Singh

Albert Einstein, Albert Michelson, All science is either physics or stamp collecting, Andrew Wiles, anthropic principle, Arthur Eddington, Astronomia nova, Brownian motion, carbon-based life, Cepheid variable, Chance favours the prepared mind, Commentariolus, Copley Medal, cosmic abundance, cosmic microwave background, cosmological constant, cosmological principle, dark matter, Dava Sobel, Defenestration of Prague, discovery of penicillin, Dmitri Mendeleev, Edmond Halley, Edward Charles Pickering, Eratosthenes, Ernest Rutherford, Erwin Freundlich, Fellow of the Royal Society, fudge factor, Hans Lippershey, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, Henri Poincaré, horn antenna, if you see hoof prints, think horses—not zebras, Index librorum prohibitorum, invention of the telescope, Isaac Newton, Johannes Kepler, John von Neumann, Karl Jansky, Kickstarter, Louis Daguerre, Louis Pasteur, luminiferous ether, Magellanic Cloud, Murray Gell-Mann, music of the spheres, Olbers’ paradox, On the Revolutions of the Heavenly Spheres, Paul Erdős, retrograde motion, Richard Feynman, scientific mainstream, Simon Singh, Solar eclipse in 1919, Stephen Hawking, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbiased observer, Wilhelm Olbers, William of Occam

On the single occasion on which he had bowed to peer pressure, he was proved to be wrong. Later he would call the cosmological constant the greatest blunder of his entire life. As he wrote in a letter to Lemaître: ‘Since I have introduced this term I had always a bad conscience…I am unable to believe that such an ugly thing should be realised in nature.’ Although Einstein was keen to abandon his cosmic fudge factor, cosmologists who still believed in an eternal, static universe were convinced that the cosmological constant was an essential and valid part of general relativity. Even some Big Bang cosmologists had become quite fond of it and were reluctant to lose it. By retaining the cosmological constant and varying its value, they could tweak their theoretical models of the Big Bang and modify the universe’s expansion.


pages: 495 words: 154,046

The Rights of the People by David K. Shipler

affirmative action, airport security, computer age, facts on the ground, fudge factor, if you build it, they will come, illegal immigration, mandatory minimum, Mikhail Gorbachev, national security letter, Nelson Mandela, Panopticon Jeremy Bentham, RFID, risk tolerance, Ronald Reagan, Skype, Thomas L Friedman, union organizing, working poor, zero-sum game

Souter’s key point was not that the Atwater arrest was justifiable—indeed, he and the majority found it full of “gratuitous humiliations imposed by a police officer who was (at best) exercising extremely poor judgment.” But the justices did not think that one policeman’s overreaction should induce the Court to ban all such misdemeanor arrests and thus “mint a new rule of constitutional law.” The fudge factor in the text of the Fourth Amendment is the word “unreasonable,” which presents judges with latitude for indulging their predilections for or against police power. Courts have held that to be reasonable, an arrest must balance two competing factors: its intrusion on personal privacy versus its weight in promoting government interests, as O’Connor noted in her Atwater dissent. She was known as a pragmatic justice, rooted as much in the real-life impacts of decisions as in their constitutional principles.


pages: 1,351 words: 385,579

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, Berlin Wall, Bonfire of the Vanities, British Empire, Broken windows theory, business cycle, California gold rush, Cass Sunstein, citation needed, clean water, cognitive dissonance, colonial rule, Columbine, computer age, conceptual framework, 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, 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, George Santayana, ghettoisation, Gini coefficient, global village, Henri Poincaré, 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, meta-analysis, Mikhail Gorbachev, moral panic, mutually assured destruction, Nelson Mandela, open economy, Peace of Westphalia, Peter Singer: altruism, 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, Skype, Slavoj Žižek, South China Sea, Stanford marshmallow experiment, Stanford prison experiment, statistical model, stem cell, Steven Levy, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, theory of mind, transatlantic slave trade, Turing machine, twin studies, ultimatum game, uranium enrichment, Vilfredo Pareto, Walter Mischel, WikiLeaks, women in the workforce, zero-sum game

A team of statisticians led by Michael Spagat and Neil Johnson found these estimates incredible and discovered that a disproportionate number of the surveyed families lived on major streets and intersections—just the places where bombings and shootings are most likely.69 An improved study conducted by the World Health Organization came up with a figure that was a quarter of the Lancet number, and even that required inflating an original estimate by a fudge factor of 35 percent to compensate for lying, moves, and memory lapses. Their unadjusted figure, around 110,000, is far closer to the battle-death body counts.70 Another team of epidemiologists extrapolated from retrospective surveys of war deaths in thirteen countries to challenge the entire conclusion that battle deaths have declined since the middle of the 20th century.71 Spagat, Mack, and their collaborators have examined them and shown that the estimates are all over the map and are useless for tracking war deaths over time.72 What about the report of 5.4 million deaths (90 percent of them from disease and hunger) in the civil war in the Democratic Republic of the Congo?

Both from the PRIO Battle Deaths Dataset, 1946–2008, Version 3.0, http://www.prio.no/CSCW/Datasets/Armed-Conflict/Battle-Deaths/, Lacina & Gleditsch, 2005. 66. Myth of reversal in civilian war deaths: Human Security Centre, 2005, p. 75; Goldstein, 2011; Roberts, 2010; White, in press. 67. Civilian deaths in the Civil War: Faust, 2008. 68. Lancet study: Burnham et al., 2006. 69. Bias in epidemiological studies: Human Security Report Project, 2009; Johnson et al., 2008; Spagat, Mack, Cooper, & Kreutz, 2009. 70. Fudge factor: Bohannon, 2008. 71. Retrospective surveys of war deaths: Obermeyer, Murray, & Gakidou, 2008. 72. The trouble with surveys: Spagat et al., 2009. 73. Claim of 5.4 million deaths in DRC: Coghlan et al., 2008. 74. Problems with DRC estimate: Human Security Report Project, 2009. 75. Famine and disease decline during war: Human Security Report Project, 2009. 76. Lives saved by vaccination: Human Security Report Project, 2009, p. 3. 77.


pages: 603 words: 182,781

Aerotropolis by John D. Kasarda, Greg Lindsay

3D printing, air freight, airline deregulation, airport security, Akira Okazaki, Asian financial crisis, back-to-the-land, barriers to entry, Berlin Wall, big-box store, blood diamonds, borderless world, Boris Johnson, British Empire, business cycle, call centre, carbon footprint, Cesare Marchetti: Marchetti’s constant, Charles Lindbergh, Clayton Christensen, cleantech, cognitive dissonance, commoditize, conceptual framework, credit crunch, David Brooks, David Ricardo: comparative advantage, Deng Xiaoping, deskilling, digital map, disruptive innovation, edge city, Edward Glaeser, failed state, food miles, Ford paid five dollars a day, Frank Gehry, fudge factor, full employment, future of work, Geoffrey West, Santa Fe Institute, George Gilder, global supply chain, global village, gravity well, Haber-Bosch Process, Hernando de Soto, hive mind, if you build it, they will come, illegal immigration, inflight wifi, intangible asset, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), intermodal, invention of the telephone, inventory management, invisible hand, Jane Jacobs, Jeff Bezos, Joan Didion, Kangaroo Route, Kickstarter, knowledge worker, kremlinology, low cost airline, Marchetti’s constant, Marshall McLuhan, Masdar, mass immigration, McMansion, megacity, Menlo Park, microcredit, Network effects, New Economic Geography, new economy, New Urbanism, oil shale / tar sands, oil shock, peak oil, Pearl River Delta, Peter Calthorpe, Peter Thiel, pets.com, pink-collar, pre–internet, RFID, Richard Florida, Ronald Coase, Ronald Reagan, Rubik’s Cube, savings glut, Seaside, Florida, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, spinning jenny, starchitect, stem cell, Steve Jobs, supply-chain management, sustainable-tourism, telepresence, the built environment, The Chicago School, The Death and Life of Great American Cities, The Nature of the Firm, thinkpad, Thomas L Friedman, Thomas Malthus, Tony Hsieh, trade route, transcontinental railway, transit-oriented development, traveling salesman, trickle-down economics, upwardly mobile, urban planning, urban renewal, urban sprawl, walkable city, white flight, white picket fence, Yogi Berra, zero-sum game

DFW annually handles some sixty million passengers, equal to one in five Americans. Heathrow sees more traffic than Britain has citizens. The world’s busiest hub, Atlanta’s Hartsfield-Jackson, has a daytime population larger than Orlando’s and an annual one that would rank it as the twelfth most populous nation on earth. (It’s also the state of Georgia’s largest employer.) All of these figures have a sky-high fudge factor, failing to account for fliers counted twice or more. The media research firm Arbitron made a better measurement a few years ago. It estimated ninety-two million Americans—nearly one in three—had flown at least once in the past twelve months. A clear and bright line separates those of us who fly and those of us who don’t. The former are almost twice as likely to make more than $100,000 a year, and more than half have incomes of $50,000 and up, compared to barely a third of the latter.


pages: 819 words: 181,185

Derivatives Markets by David Goldenberg

Black-Scholes formula, Brownian motion, capital asset pricing model, commodity trading advisor, compound rate of return, conceptual framework, correlation coefficient, Credit Default Swap, discounted cash flows, discrete time, diversification, diversified portfolio, en.wikipedia.org, financial innovation, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, law of one price, locking in a profit, London Interbank Offered Rate, Louis Bachelier, margin call, market microstructure, martingale, Myron Scholes, Norbert Wiener, Paul Samuelson, price mechanism, random walk, reserve currency, risk/return, riskless arbitrage, Sharpe ratio, short selling, stochastic process, stochastic volatility, time value of money, transaction costs, volatility smile, Wiener process, yield curve, zero-coupon bond, zero-sum game

However, these changes would have to be equal in order for a one-for-one hedge to be able to replicate the option, no matter what the bond position. In order to hedge the option in the Binomial model, we have to have a hedge ratio different from 1, except for Case 1. Further, it generally has to be less than 1.0 in order to hedge the option. When we replicated the option for European Put-Call Parity, we also had a European put option that we used as the ‘fudge’ factor. Here, we only have the stock and the bond. So we have to do better than we did in proving European Put-Call Parity. How can we do better, given that we lost the put option? The answer is that we have been given something we didn’t have for proving European Put-Call Parity. We now get to choose the hedge ratio and make it different from 1.0. (We also get to change the hedge ratio in the Binomial model for N>1 as the underlying stock price changes, and thereby dynamically hedge the option.)


pages: 829 words: 186,976

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

"Robert Solow", airport security, availability heuristic, Bayesian statistics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Swan, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Freestyle chess, fudge factor, George Akerlof, global pandemic, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, PageRank, pattern recognition, pets.com, Pierre-Simon Laplace, prediction markets, Productivity paradox, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, wikimedia commons

* Meditation helps people achieve this, in part, by encouraging focus on posture and breathing—things that are within our control but which we normally take for granted. * Some of it also represents market making: certain investment firms, like a well-stocked 7-Eleven, hold a lot of inventory and can be counted on to be open for business when no one else is, hoping to make a few pennies at a time for their trouble. * One could imagine that a small fudge factor might be allowed if our probability estimates were close but not exactly the same, since there is some inconvenience associated with betting. * I met Santorum for my New York Times story on the Iowa vote count dispute after the initial tally had shown Romney ahead. Santorum remembered my bet and jokingly asserted that the bet was my motivation for tracking him down. It may have provided some additional incentive


pages: 706 words: 206,202

Den of Thieves by James B. Stewart

corporate raider, creative destruction, discounted cash flows, diversified portfolio, fixed income, fudge factor, George Gilder, index arbitrage, Internet Archive, Irwin Jacobs, margin call, money market fund, Ponzi scheme, rolodex, Ronald Reagan, shareholder value, South Sea Bubble, The Predators' Ball, walking around money, zero-coupon bond

But it was no secret that Boesky, given the enormous size of his positions and his insatiable quest for greater leverage, was constantly in danger of violating the regulatory net capital requirements. Boesky and many arbitrageurs had always viewed the net capital requirements with thinly veiled contempt. His colleagues Conway and especially Mooradian, who had nearly lost his career after being disci- plined for net capital violations, took the law much more seriously and tried to keep Boesky in compliance. They even went so far as to build in what they termed a "fudge factor" that overstated Boesky's actual leverage in order to try to keep him in bounds. In 1985, however, with the pace of merger deals quickening, and the resulting increase in arbitrage opportunities, it was getting harder and harder to keep Boesky in compliance. Finally, that summer, Conway wrote Boesky an angry memo: "You have continued to show very small regard for our net capital position or the debt covenants under our loan agreements. . . .


pages: 665 words: 207,115

Across Realtime by Vernor Vinge

fudge factor, gravity well, Isaac Newton, job automation, Magellanic Cloud, means of production, technological singularity, Vernor Vinge

It was more like seventy-five minutes than an hour. Since the Age of Man, the Earth's rotation had slowed. Now, at fifty megayears, the day was a little over twenty-five hours long. Rather than change the definition of -he second or the hour, the Korolevs had decreed (just another of their decrees) that the standard day should consist of twenty-four hours plus whatever time it took to complete one rotation. Yel‚n called the extra time the Fudge Factor. Everyone else ailed it the Witching Hour. Wil walked through the Witching Hour, looking for some sign of Marta Korolev. He was still on the Robinson estate, that.vas obvious: as advanced travelers, the Robinsons had plenty of robots. Rescue-day ash had been meticulously cleaned from he stone seats, the fountains, the trees, even the ground. The.cent of almost-jacarandas floated in the cool night breeze.


pages: 698 words: 198,203

The Stuff of Thought: Language as a Window Into Human Nature by Steven Pinker

airport security, Albert Einstein, Bob Geldof, colonial rule, conceptual framework, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Douglas Hofstadter, en.wikipedia.org, experimental subject, fudge factor, George Santayana, Laplace demon, loss aversion, luminiferous ether, Norman Mailer, Richard Feynman, Ronald Reagan, Sapir-Whorf hypothesis, science of happiness, social intelligence, speech recognition, stem cell, Steven Pinker, Thomas Bayes, Thorstein Veblen, traffic fines, urban renewal, Yogi Berra

As with real epidemics, it’s hard to predict what will happen. Depending on small differences in how catchy the word is, and on how well-connected, trusted, or charismatic its first adopters are, it may or may not reach the tipping point that would lead it to become entrenched in the community and perpetuated down the generations. 54 This is a way to make sense of the Frequency and Diversity components of the FUDGE factors that Metcalfe suggests are the secrets to a word’s success. So a look at the spread of words and names upends the conventional wisdom of where culture comes from and how it changes. In the twentieth century, a culture came to be thought of as a superorganism that pursues goals, finds meaning, responds to stimuli, and can be the victim of manipulation or the beneficiary of intervention. But the fortunes of names, a cultural practice par excellence, doesn’t fit that model.


pages: 1,261 words: 294,715

Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky

autonomous vehicles, Bernie Madoff, biofilm, blood diamonds, British Empire, Broken windows theory, Brownian motion, car-free, clean water, cognitive dissonance, corporate personhood, corporate social responsibility, Daniel Kahneman / Amos Tversky, delayed gratification, desegregation, different worldview, double helix, Drosophila, Edward Snowden, en.wikipedia.org, epigenetics, Flynn Effect, framing effect, fudge factor, George Santayana, global pandemic, hiring and firing, illegal immigration, impulse control, income inequality, John von Neumann, Loma Prieta earthquake, long peace, longitudinal study, loss aversion, Mahatma Gandhi, meta analysis, meta-analysis, Mohammed Bouazizi, Monkeys Reject Unequal Pay, mouse model, mutually assured destruction, Nelson Mandela, Network effects, out of africa, Peter Singer: altruism, phenotype, placebo effect, publication bias, RAND corporation, risk tolerance, Rosa Parks, selective serotonin reuptake inhibitor (SSRI), self-driving car, Silicon Valley, social intelligence, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steven Pinker, strikebreaker, theory of mind, transatlantic slave trade, traveling salesman, trickle-down economics, twin studies, ultimatum game, Walter Mischel, wikimedia commons, zero-sum game

When deaths are expressed as a percentage of total population, World War II is the only twentieth-century event cracking the top ten, behind An Lushan, the Mongol conquests, the Mideast slave trade, the fall of the Ming dynasty, the fall of Rome, the deaths caused by Tamerlane, the annihilation of Native Americans by Europeans, and the Atlantic slave trade. Critics have questioned this—“Hey, stop using fudge factors to somehow make World War II’s 55 million dead less than the fall of Rome’s 8 million.” After all, 9/11’s murders would not have evoked only half as much terror if America had 600 million instead of 300 million citizens. But Pinker’s analysis is appropriate, and analyzing rates of events is how you discover that today’s London is much safer than was Dickens’s or that some hunter-gatherer groups have homicide rates that match Detroit’s.


pages: 1,535 words: 337,071

Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley, Jon Kleinberg

Albert Einstein, AltaVista, clean water, conceptual framework, Daniel Kahneman / Amos Tversky, Douglas Hofstadter, Erdős number, experimental subject, first-price auction, fudge factor, George Akerlof, Gerard Salton, Gerard Salton, Gödel, Escher, Bach, incomplete markets, information asymmetry, information retrieval, John Nash: game theory, Kenneth Arrow, longitudinal study, market clearing, market microstructure, moral hazard, Nash equilibrium, Network effects, Pareto efficiency, Paul Erdős, planetary scale, prediction markets, price anchoring, price mechanism, prisoner's dilemma, random walk, recommendation engine, Richard Thaler, Ronald Coase, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, Simon Singh, slashdot, social web, Steve Jobs, stochastic process, Ted Nelson, The Market for Lemons, The Wisdom of Crowds, trade route, transaction costs, ultimatum game, Vannevar Bush, Vickrey auction, Vilfredo Pareto, Yogi Berra, zero-sum game

used initially as well. And indeed, it suffers from exactly this problem — advertisers can sometimes occupy high slots without generating much money for the search engine. The role of ad quality. When Google developed its system for advertising, it addressed this problem as follows. For each ad submitted by an advertiser j, they determine an estimated quality factor qj. This is intended as a “fudge factor” on the clickthrough rate: if advertiser j appears in slot i, then the clickthrough rate is estimated to be not ri but the product qjri. The introduction of ad quality is simply a generalization of the model we’ve been studying all along: in particular, if we assume that all factors qi are equal to 1, then we get back the model that we’ve been using thus far in the chapter. From the perspective of our matching market formulation, it’s easy to incorporate these quality factors: we simply change the valuation of advertiser j for slot i, from vij = rivj to vij = qjrivj.


pages: 1,445 words: 469,426

The Prize: The Epic Quest for Oil, Money & Power by Daniel Yergin

anti-communist, Ayatollah Khomeini, bank run, Berlin Wall, British Empire, colonial exploitation, Columbine, continuation of politics by other means, cuban missile crisis, do-ocracy, energy security, European colonialism, Exxon Valdez, financial independence, fudge factor, informal economy, joint-stock company, land reform, liberal capitalism, megacity, Mikhail Gorbachev, Monroe Doctrine, new economy, North Sea oil, oil rush, oil shale / tar sands, oil shock, old-boy network, postnationalism / post nation state, price stability, RAND corporation, rent-seeking, Ronald Reagan, shareholder value, Thomas Malthus, Yom Kippur War

Yet before any agreements could be made, several fundamental issues had to be thrashed out, including the basic question of valuation. For instance, depending on the accounting formula that was chosen, 25 percent of the Kuwait Oil Company could be worth anywhere from sixty million to one billion dollars. Finally, in that case, the two sides came together by inventing a new accounting concept, "updated book value," which included inflation and large fudge factors. And in October 1972 a "participation agreement" was finally reached between the Gulf states and the companies. It provided for an immediate 25 percent participation share, rising to 51 percent by 1983. But, despite all the OPEC endorsements, the application of the agreement was less popular in the rest of OPEC than Yamani hoped. Algeria, Libya, and Iran all stood outside it. Kuwait's oil minister approved it, but the Kuwaiti parliament rejected it, and so Kuwait was also out.