Posts Tagged 'Probability'

Limits of Sequences, Limits of Sets

Karl Weierstrass (1815–1897).

In undergraduate mathematics, we are confronted at an early stage with “Epsilon-Delta” definitions. For example, given a function {f(x)} of a real variable, we may ask what is the value of the function for a particular value {x=a}. Maybe this is an easy question or maybe it is not.

The epsilon-delta concept can be subtle, and is sufficiently difficult that it has been used as a filter to weed out students who may not be considered smart enough to continue in maths (I know this from personal experience). The formulation of the epsilon-delta definitions is usually attributed to the German mathematician Karl Weierstrass. They must have caused him many sleepless nights.

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Benford’s Law Revisited

{Probability for the first decimal digit {D_1} of a number to take values from 1 to 9.

Several researchers have observed that, in a wide variety of collections of numerical data, the leading — or most significant — decimal digits are not uniformly distributed, but conform to a logarithmic distribution. Of the nine possible values, {D_1=1} occurs more than {30\%} of the time while {D_1=9} is found in less than {5\%} of cases (see Figure above). Specifically, the probability distribution is

\displaystyle \mathsf{P}(D_1 = d) = \log_{10} \left( 1 + \frac{1}{d} \right) \,, \quad \mbox{ for\ } d = 1, 2, \dots , 9 \,. \ \ \ \ \ (1)

A more complete form of the law gives the probabilities for the second and subsequent digits. A full discussion of Benford’s Law is given in Berger and Hill (2015).

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Bernoulli’s Golden Theorem and the Law of Large Numbers

Swiss postage stamp, issued in 1994 for the International Congress of Mathematicians in Zurich, featuring Jakob Bernoulli and illustrating his “golden theorem”.

Jakob Bernoulli, head of a dynasty of brilliant scholars, was one of the world’s leading mathematicians. Bernoulli’s great work, Ars Conjectandi, published in 1713, included a profound result that he established “after having meditated on it for twenty years”. He called it his “golden theorem”. It is known today as the law of large numbers, and it was the first limit theorem in probability, and the first attempt to apply probability outside the realm of games of chance [TM225 or search for “thatsmaths” at irishtimes.com].

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Think of a Number: What are the Odds that it is Even?

Pick a positive integer at random. What is the chance of it being 100? What or the odds that it is even? What is the likelihood that it is prime?

EulerProbDist

Probability distribution {P(n)=1/(\zeta(s)n^s)} for s=1.1 (red), s=1.01 (blue) and s=1.001 (black).

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How many numbers begin with a 1? More than 30%!

The irregular distribution of the first digits of numbers in data-bases provides a valuable tool for fraud detection. A remarkable rule that applies to many datasets was accidentally discovered by an American physicist, Frank Benford, who described his discovery in a 1938 paper, “The Law of Anomalous Numbers” [TM181 or search for “thatsmaths” at irishtimes.com].

Benford-Distribution-3

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The Two Envelopes Fallacy

During his Hamilton lecture in Dublin recently, Fields medalist Martin Hairer made a passing mention of the “Two Envelopes Paradox”. This is a well-known problem in probability theory that has led to much misunderstanding. It was originally developed in 1912 by the leading German number theorist Edmund Landau (see Gorroochurn, 2012). It is frequently discussed on the web, with much misunderstanding and confusion. I will try to avoid adding to that.

Two-Envelopes

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The Improbability Principle

Extremely improbable events are commonplace.

It’s an unusual day if nothing unusual happens”. This aphorism encapsulates a characteristic pattern of events called the Improbability Principle. Popularised by statistician Sir David Hand, emeritus professor at Imperial College London, it codifies the paradoxical idea that extremely improbable events happen frequently.  [TM112 or search for “thatsmaths” at irishtimes.com].

Improbability-Principle-Top

From front cover of  The Improbability Principle

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Treize: A Card-Matching Puzzle

Probability theory is full of surprises. Possibly the best-known paradoxical results are the Monty Hall Problem and the two-envelope problem, but there are many others. Here we consider a simple problem using playing cards, first analysed by Pierre Raymond de Montmort (1678–1719).

SpadesHearts

Shuffle spades in one pile, hearts in another. Place both piles face downwards. Turn over a card from each pile. Do the two cards match?

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Twenty Heads in Succession: How Long will we Wait?

If three flips of a coin produce three heads, there is no surprise. But if 20 successive heads show up, you should be suspicious: the chances of this are less than one in a a million, so it is more likely than not that the coin is unbalanced.

euro-frontback-ie

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Random Harmonic Series

We consider the convergence of the random harmonic series

\displaystyle R = \sum_{n=1}^{\infty}\frac{\sigma_{n}}{n}

where {\sigma_n\in\{-1,+1\}} is chosen randomly with probability {1/2} of being either plus one or minus one. It follows from the Kolmogorov three-series theorem that the series is “almost surely” convergent.

RandomHarmonicSeriesDistribution

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Bertrand’s Chord Problem

The history of probability theory has been influenced strongly by paradoxes, results that seem to defy intuition. Many of these have been reviewed in a recent book by Prakash Gorroochurn [2012]. We will have a look at Bertrand’s Paradox (1889), a simple result in geometric probability.

Bertrand-00Let’s start with an equilateral triangle and add an inscribed circle and a circumscribed circle. It is a simple geometric result that the radius of the outer circle is twice that of the inner one. Bertrand’s problem may be stated thus:

Problem: Given a circle, a chord is drawn at random. What is the probability that the chord length is greater than the side of an equilateral triangle inscribed in the circle?

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Franc-carreau or Fair-square

Franc-carreau is a simple game of chance, like the roll-a-penny game often seen at fairs and fêtes. A coin is tossed or rolled down a wooden chute onto a large board ruled into square segments. If the player’s coin lands completely within a square, he or she wins a coin of equal value. If the coin crosses a dividing line, it is lost.

Franc-Carreau-01

The playing board for Franc-Carreau is shown above, together with a winning coin (red) contained within a square and a loosing one (blue) crossing a line. As the precise translation of franc-carreau appears uncertain, the name “fair square” would seem appropriate.

The question is: What size should the coin be to ensure a 50% chance of winning?

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Twin Peaks Entropy

Next week there will be a post on tuning pianos using a method based on entropy. In preparation for that, we consider here how the entropy of a probability distribution function with twin peaks changes with the separation between the peaks.

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Buffon was no Buffoon

The Buffon Needle method of estimating {\pi} is hopelessly inefficient. With one million throws of the needle we might expect to get an approximation accurate to about three digits. The idea is more of philosophical than of practical interest. Buffon never envisaged it as a means of computing {\pi}.

Image drawn with Mathematica package in: Siniksaran, Erin, 2008: Throwing Buffon’s Needle [Reference below].

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Bent Coins: What are the Odds?

If we toss a `fair’ coin, one for which heads and tails are equally likely, a large number of times, we expect approximately equal numbers of heads and tails. But what is `approximate’ here? How large a deviation from equal values might raise suspicion that the coin is biased? Surely, 12 heads and 8 tails in 20 tosses would not raise any eyebrows; but 18 heads and 2 tails might.

Bent-Coin-2 Continue reading ‘Bent Coins: What are the Odds?’

The Faraday of Statistics

This week, That’s Maths in The Irish Times ( TM044 ) is about the originator of Students t-distribution.

In October 2012 a plaque was unveiled at St Patrick’s National School, Blackrock, to commemorate William Sealy Gosset, who had lived nearby for 22 years. Sir Ronald Fisher, a giant among statisticians, called Gosset “The Faraday of Statistics”, recognising his ability to grasp general principles and apply them to problems of practical significance.

Plaque at St Patrick's National School, Hollypark, Blackrock, where William Gosset lived from 1913 to 1935.

Plaque at St Patrick’s National School, Hollypark, Blackrock, where William Gosset lived from 1913 to 1935.

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Breaking Weather Records

In arithmetic series, like 1 + 2 + 3 + 4 + 5 + … , each term differs from the previous one by a fixed amount. There is a formula for calculating the sum of the first N terms. For geometric series, like 3 + 6 + 12 + 24 + … , each term is a fixed multiple of the previous one. Again, there is a formula for the sum of the first N terms of such a series. Continue reading ‘Breaking Weather Records’

Bayes Rules OK

This week, That’s Maths ( TM018 ) deals with the “war” between Bayesians and frequentists, a long-running conflict that has now subsided. It is 250 years since the presentation of Bayes’ results to the Royal Society in 1763.

The column below was inspired by a book, The Theory that would not Die, by Sharon Bertsch McGrayne, published by Yale University Press in 2011.
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