Joan R. Ginther who won lottery 4 times is a Stanford University statistics PhD | Mail Online
By Daniel Miessler on August 19th, 2011: Tagged as Mathematics
First, she won $5.4 million, then a decade later, she won $2million, then two years later $3million and in the summer of 2010, she hit a $10million jackpot.
The odds of this has been calculated at one in eighteen septillion and luck like this could only come once every quadrillion years.
Harper’s reporter Nathanial Rich recently wrote an article about Ms Ginther, which calls the the validity of her ‘luck’ into question.
First, he points out, Ms Ginther is a former math professor with a PhD from Stanford University specialising in statistics.
A professor at the Institute for the Study of Gambling & Commercial Gaming at the University of Nevada, Reno, told Mr Rich: ‘When something this unlikely happens in a casino, you arrest ‘em first and ask questions later.’
Math pays.
Mysterious number 6174 | plus.maths.org
By Daniel Miessler on June 7th, 2011: Tagged as Mathematics
The number 6174 is a really mysterious number. At first glance, it might not seem so obvious. But as we are about to see, anyone who can subtract can uncover the mystery that makes 6174 so special.
Kaprekar’s operation
In 1949 the mathematician D. R. Kaprekar from Devlali, India, devised a process now known as Kaprekar’s operation. First choose a four digit number where the digits are not all the same (that is not 1111, 2222,…). Then rearrange the digits to get the largest and smallest numbers these digits can make. Finally, subtract the smallest number from the largest to get a new number, and carry on repeating the operation for each new number.
It is a simple operation, but Kaprekar discovered it led to a surprising result. Let’s try it out, starting with the number 2005, the digits of last year. The maximum number we can make with these digits is 5200, and the minimum is 0025 or 25 (if one or more of the digits is zero, embed these in the left hand side of the minimum number). The subtractions are:
5200 – 0025 = 5175
7551 – 1557 = 5994
9954 – 4599 = 5355
5553 – 3555 = 1998
9981 – 1899 = 8082
8820 – 0288 = 8532
8532 – 2358 = 6174
7641 – 1467 = 6174
Fascinating.
Lord Russell’s Nightmare | The Big Questions
By Daniel Miessler on December 21st, 2010: Tagged as Mathematics
Having determined to write the Principia ten years earlier in 1900, Russell was at first stymied by his discovery of the famous paradox that now bears his name: Consider the set of all those sets that don’t contain themselves. Call this set R. Does R contain itself? If so, it belongs to the set of all sets that don’t contain themselves, and therefore does not contain itself. Does it fail to contain itself? If so, it fails to belong to the set of all sets that don’t contain themselves, and therefore contains itself. Either way, something’s screwy.
Carl?
The Joy of Stats | BBC
By Daniel Miessler on December 20th, 2010: Tagged as Mathematics
The Allais Paradox | Wired Science | Wired.com
By Daniel Miessler on October 22nd, 2010: Tagged as Mathematics | Science
Maurice Allais, a Nobel prize winning economist, died earlier this month. In this post, I’m going to focus on one of his many intellectual contributions, as it profoundly influenced modern psychology. It’s known as the Allais Paradox, and it was first outlined in a 1953 Econometrica article. Here’s an example of the paradox:
Suppose somebody offered you a choice between two different vacations. Vacation number one gives you a 50 percent chance of winning a three-week tour of England, France and Italy. Vacation number two offers you a one-week tour of England for sure.
Not surprisingly, the vast majority of people (typically over 80 percent) prefer the one-week tour of England. We almost always choose certainty over risk, and are willing to trade two weeks of vacation for the guarantee of a one-week vacation. A sure thing just seems better than a gamble that might leave us with nothing. But how about this wager:
Vacation number one offers you a 5 percent chance of winning a three week tour of England, France and Italy. Vacation number two gives you a 10 percent chance of winning a one week tour of England.
In this case, most people choose the three-week trip. We figure both vacations are unlikely to happen, so we might as well go for broke on the grand European tour. (People act the same way with lotteries: we typically buy the ticket for the biggest possible prize, regardless of the odds.)
A 4-D Cube
By Daniel Miessler on August 30th, 2010: Tagged as Mathematics
A Calculus Analogy: Integrals as Multiplication | BetterExplained
By Daniel Miessler on July 5th, 2010: Tagged as Mathematics
Integrals are often described as finding the “area under the curve”. This description is misleading, like saying multiplication is for finding “the area of a rectangle”. Finding area is a useful property, but not the purpose. Integrals help us combine numbers when multiplication can’t.
Math Class Needs A Makeover | Dan Meyer, TED
By Daniel Miessler on June 30th, 2010: Tagged as Mathematics
On Average, Mean, Median, and Mode
By Daniel Miessler on June 28th, 2010: Tagged as Mathematics

If you’re reading this you’re probably a bit geeky (like me), and you’ve no doubt been in at least 42 conversations about average vs. mean, etc, etc. So here’s a good summary of the basics for next time.
First Things First: “Average” is a General Term
If you’ve ever been lobbed the question of “what’s the difference between the average and the mean?”, you (and perhaps the questioner too) might have fallen into a trap. A mean is a type of average, not an alternative to one.
- average
- - An average is a single value that is meant to typify a list of values.
Average is a general class. It just means “let’s try and generalize the data given a set of data points”, and the (basic) mechanics for actually doing so are described with three other terms: *mean*, *median*, and *mode*.
- mean
- - A mean is attained by adding all values and dividing by the total number of values.
Hey, wait–that sounds like an average, right? That’s because it is. That’s the whole point–they’re the same. A mean is a type of average, so when people are asked to give an average (a general idea of the data) they often give the mean. And what about median and mode?
- median
- - A median is described as the numeric value separating the higher half of a sample, a population, or a probability distribution, from the lower half.
Simple enough. And what about mode?
- mode
- - The mode is the value that occurs the most frequently in a data set or a probability distribution.
Summary
Means, medians, and modes are all types of averages. A mean is the one where you add them all up and divide by the number of values, the median is the value that separates the top half and bottom half, and the mode is the value that is found most frequently in the set. ::
Notes
1 [ For more reading, do visit the averages page at Wikipedia. ]
