John D. Cook

The Lindy effect says that what’s been around the longest is likely to remain around the longest. It applies to creative artifacts, not living things. A puppy is likely to live longer than an elderly dog, but a book that has been in press for a century is likely to be in press for another century. […]

The previous post gave an example of manipulating the seed of a random number generator to produce a desired result. This post will do something similar for a different generator. A couple times I’ve used the following LCG (linear congruential random number generator) in examples. An LCG starts with an initial value of z and updates z […]

With some random number generators, it’s possible to select the seed carefully to manipulate the output. Sometimes this is easy to do. Sometimes it’s hard but doable. Sometimes it’s theoretically possible but practically impossible. In my recent correspondence with Melissa O’Neill, she gave me an example that seeds a random number generator so that the […]

PractRand is a random number generator test suite, somewhat like the DIEHARDER and NIST tests I’ve written about before, but more demanding. Rather than running to completion, it runs until it a test fails with an infinitesimally small p-value. It runs all tests at a given sample size, then doubles the sample and runs the tests again. […]

I just ran across a post by John Baez pointing to an article by Alan Frieze on random minimum spanning trees. Here’s the problem. Create a complete graph with n nodes, i.e. connect every node to every other node. Assign each edge a uniform random weight between 0 and 1. Find the minimum spanning tree. Add up […]

You can select blocks of text in Emacs just as you would in most other environments. You could, for example, drag your mouse over a region. You could also hold down the Shift key and use arrow keys. But Emacs also has a number of commands that let you work in larger semantic units. That […]

The previous post was a riff on a tweet asking what you’d get if you extracted all the i‘s, j‘s, and k‘s from Finnegans Wake and multiplied them as quaternions. This post is a probabilistic variation on the previous one. If you randomly select a piece of English prose, extract the i‘s, j‘s, and k‘s, and multiply them together as quaternions, what […]

I stumbled on a Twitter account yesterday called Wolfram|Alpha Can’t. It posts bizarre queries that Wolfram Alpha can’t answer. Here’s one that caught my eye. result of extracting the i’s, j’s, and k’s in order from Finnegans Wake and interpreting as a quaternion product — Wolfram|Alpha Can’t (@wacnt) May 17, 2017 Suppose you did extract […]

There are five regular solids in three dimensions: tetrahedron octahedron (pictured above) hexahedron (cube) dodecahedron icosahedron. I give a proof here that these are the only five. The first three of these regular solids generalize to all dimensions, and these generalizations are the only regular solids in dimensions 5 and higher. (There are six regular […]

From Nick Patterson’s interview on Talking Machines: GCHQ in the ’70s, we thought of ourselves as completely Bayesian statisticians. All our data analysis was completely Bayesian, and that was a direct inheritance from Alan Turing. I’m not sure this has ever really been published, but Turing, almost as a sideline during his cryptoanalytic work, reinvented […]

The previous couple blog posts touched on a special case of sphere packing. We looked at the proportion of volume contained near the corners of a hypercube. If you take the set of points within a distance 1/2 of a corner of a hypercube, you could rearrange these points to form a full ball centered […]

I’ve written a couple blog posts that may seem to contradict each other. Given a high-dimensional cube, is most of the volume in the corners or not? I recently wrote that the corners of a cube stick out more in high dimensions. You can quantify this by centering a ball at a corner and looking […]

High-dimensional geometry is full of surprises. For example, nearly all the area of a high-dimensional sphere is near the equator, and by symmetry it doesn’t matter which equator you take. Here’s another surprise: corners stick out more in high dimensions. Hypercubes, for example, become pointier as dimension increases. How might we quantify this? Think of […]

I updated several of the math diagrams on this site today. They’re SVG now, so they resize nicely if you want to zoom in our out. Special functions Topological vector spaces Category theory concepts General topology Gamma function identities

The previous post looked at a continuous example of concentration of measure. As you move away from a thin band around the equator, the remaining area in the rest of the sphere decreases as an exponential function of the dimension and the distance from the equator. This post will show a very similar result for […]

Nearly all the area of a high-dimensional sphere is near the equator. And by symmetry, it doesn’t matter which equator you take. Draw any great circle and nearly all of the area will be near that circle. This is the canonical example of “concentration of measure.” What exactly do we mean by “nearly all the […]

A few days ago I wrote about testing the PCG random number generator using the DIEHARDER test suite. In this post I’ll go into a little more background on this random number generator test suite. I’ll also show that like M. E. O’Neill’s PCG (“permuted congruential generator”), George Marsaglia’s MWC (“multiply with carry”) generator does quite […]

The chaos game is played as follows. Pick a starting point at random. Then at each subsequent step, pick a triangle vertex at random and move half way from the current position to that vertex. The result looks like a fractal called the Sierpinski triangle or Sierpinski gasket. Here’s an example: If the random number […]

M. E. O’Neill’s PCG family of random number generators looks very promising. It appears to have excellent statistical and cryptographic properties. And it takes remarkably little code to implement. (PCG stands for Permuted Congruential Generator.) The journal article announcing PCG gives the results of testing it with the TestU01 test suite. I wanted to try it out […]

I was running the NIST statistical test suite recently. I wanted an example of a random number generator where the tests failed, and so I used a simple generator, a linear congruence generator. But to my surprise, the generator passed nearly all the tests, even though some more sophisticated generators failed some of the same […]

Here’s a surprising result: The least common multiple of the first n positive integers is approximately exp(n). More precisely, let φ(n) equal the log of the least common multiple of the numbers 1, 2, …, n. There are theorems that give upper and lower bounds on how far φ(n) can be from n. We won’t prove or […]

You can subscribe to my blog by email or RSS. I also have a brief newsletter you could sign up for. There are links to these in the sidebar of the blog: If you subscribe by email, you’ll get an email each morning containing the post(s) from the previous day. I just noticed a problem […]

In applications we’d like to draw independent random samples from complicated probability distributions, often the posterior distribution on parameters in a Bayesian analysis. Most of the time this is impractical. MCMC (Markov Chain Monte Carlo) gives us a way around this impasse. It lets us draw samples from practically any probability distribution. But there’s a […]

The average number of operations needed for quicksort to sort a list of n items is approximately 10 times the nth prime number. Here’s some data to illustrate this. |------+-----------------+---------| | n | avg. operations | 10*p(n) | |------+-----------------+---------| | 100 | 5200.2 | 5410 | | 200 | 12018.3 | 12230 | | 300 | 19446.9 […]

Suppose you’re tracking some object based on its initial position x0 and initial velocity v0. The initial position and initial velocity are estimated from normal distributions with standard deviations σx and σv. (To keep things simple, let’s assume our object is moving in only one dimension and that the distributions around initial position and velocity […]

Let p(x) = a0 + a1x + a2x2 + … + anxn and suppose at least one of the coefficients ai is irrational for some i ≥ 1. Then a theorem by Weyl says that the fractional parts of p(n) are equidistributed as n varies over the integers. That is, the proportion of values that land in some interval […]

The first digit of a power of 2 is a 1 more often than any other digit. Powers of 2 begin with 1 about 30% of the time. This is because powers of 2 follow Benford’s law. We’ll prove this below. When is the first digit of 2n equal to k? When 2n is between […]

A beta probability distribution has two parameters, a and b. You can think of these as the number of successes and failures out of a+b trials. The PDF of a beta distribution is approximately normal if a and b are approximately equal and a + b is large. If a and b are close, they don’t have to be very large for the beta […]

A function f: X → X is measure-preserving if for each iteration of f sends the same amount of stuff into a given set. To be more precise, given a measure μ and any μ-measurable set E with μ(E) > 0, we have μ( E ) = μ( f –1(E) ). You can read the right side of […]

These have been the most popular posts for the first half of 2017. Golden powers are nearly integers How efficient is Morse code? Putting SHA1 in perspective Improving on the Unix shell Three proofs that 2017 is prime How areas of math are connected

Arguments in favor of functional programming are often unconvincing. For example, the most common argument is that functional programming makes it easier to “reason about your code.” That’s true to some extent. All other things being equal, it’s easier to understand a function if all its inputs and outputs are explicit. But all other things […]

If you’ve read this blog for long, you know that my work is a combination of math, statistics, and computing. I was looking over my records and tried to see how my work divides into these three areas. In short, it doesn’t. The boundaries between these areas are fuzzy or arbitrary to begin with, but […]

The Gaussian correlation inequality was proven in 2014, but the proof only became widely known this year. You can find Thomas Royan’s remarkably short proof here. Let X be a multivariate Gaussian random variable with mean zero and let E and F be two symmetric convex sets, both centered at the origin. The Gaussian correlation inequality says that Prob(X in E […]

In a blog post yesterday, I mentioned that the golden angle is an irrational portion of a circle, and so a sequence of rotations by the golden angle will not repeat itself. We can say more: rotations by an irrational portion of a circle are ergodic. Roughly speaking, this means that not only does the […]

Last year I wrote a post about saxophone octave keys. I was surprised to discover, after playing saxophone for most of my life, that a saxophone has not one but two octave holes. Modern saxophones have one octave key, but two octave holes. Originally saxophones had a separate octave key for each octave hole; you had to […]

The other day I wrote about the golden angle, a variation on the golden ratio. If φ is the golden ratio, then a golden angle is 1/φ2 of a circle, approximately 137.5°, a little over a third of a circle. Musical notes go around in a circle. After 12 half steps we’re back where we […]

Here’s a script I wanted to write: given a color c specified in RGB and an angle θ, rotate c on the color wheel by θ and return the RGB value of the result. You can’t rotate RGB values per se, but you can rotate hues. So my initial idea was to convert RGB to […]

From Paul Phillips: I see adjoint functors. How often do you see them? All the time. They’re everywhere. pic.twitter.com/6PkGJ9wP4A — Paul Phillips (@contrarivariant) May 27, 2017 Mashup of Saunders Mac Lane’s quip “Adjoint functors arise everywhere” and Haley Joel Osment’s famous line from Sixth Sense. Related: Applied category theory

“Teachers should prepare the student for the student’s future, not for the teacher’s past.” — Richard Hamming I ran across the above quote from Hamming this morning. It made me wonder whether I tried to prepare students for my past when I used to teach college students. How do you prepare a student for the […]

From Foundations of Algebraic Geometry: … in an ideal world, people would learn this material over many years, after having background courses in commutative algebra, algebraic topology, differential geometry, complex analysis, homological algebra, number theory, and French literature.

From Dorothy Sayers’ essay Why Work? It is always strange and painful to have to change a habit of mind; though, when we have made the effort, we may find a great relief, even a sense of adventure and delight, in getting rid of the false and returning to the true.

Start with a rose, as described in the previous post: Now spin that rose around a vertical line a distance R from the center of the rose. This makes a torus (doughnut) shape whose cross sections look like the rose above. You could think of having a cutout shaped like the rose above and extruding Play-Doh […]

The polar graph of r = cos(kθ) is called a rose. If k is even, the curve will trace out 2k petals as θ runs between 0 and 2π. If k is odd, it will trace out k petals, tracing each one twice. For example, here’s a rose with k = 5. (I rotated the […]

The graph of hyperbolic cosine is called a catenary. A catenary has the following curious property: the length of a catenary between two points equals the area under the catenary between those two points. The proof is surprisingly simple. Start with the following: Now integrate the first and last expressions between two points a and […]

In a high school algebra class, you learn how to solve polynomial equations in one variable, and systems of linear equations. You might reasonably ask “So when do we combine these and learn to solve systems of polynomial equations?” The answer would be “Maybe years from now, but most likely never.” There are systematic ways to […]

Different colors of noise are named by analogy with colors of light. Pink noise is between white noise and red noise. White noise has equal power at all frequencies, just as white light is a combination of all the frequencies of the visible spectrum. The components of red noise are weighted toward low frequencies, just […]

Yesterday a friend told me about a software project whose owners said “We’re going to do this the right way.” I told him I have two opposite reactions when I hear that: Ooh, that sounds like fun! Run away! I’ve been on several projects where the sponsors have identified some aspect of the status quo […]

This is the third, and last, of a series of posts on Benford’s law, this time looking at a famous open problem in computer science, the 3n + 1 problem, also known as the Collatz conjecture. Start with a positive integer n. Compute 3n + 1 and divide by 2 repeatedly until you get an odd […]

Introduction Samples from a Cauchy distribution nearly follow Benford’s law. I’ll demonstrate this below. The more data you see, the more confident you should be of this. But with a typical statistical approach, crudely applied NHST (null hypothesis significance testing), the more data you see, the less convinced you are. This post assumes you’ve read the […]

Introduction to Benford’s law In 1881, Simon Newcomb noticed that the edges of the first pages in a book of logarithms were dirty while the edges of the later pages were clean. From this he concluded that people were far more likely to look up the logarithms of numbers with leading digit 1 than of […]