Another Poorly Written Word Problem: Index

I’m doing something that I should have done a long time ago: collecting a series of posts into one single post. The following links comprised my series poorly written word problem, taken directly from textbooks and other materials from textbook publishers.

Part 1: Addition and estimation.

Part 2: Estimation and rounding.

Part 3: Probability.

Part 4: Subtraction and estimation.

Part 5: Algebra and inequality.

Part 6: Domain and range of a function.

Part 7: Algebra and inequality.

Part 8: Algebra and inequality.

 

 

My Mathematical Magic Show: Index

I’m doing something that I should have done a long time ago: collecting a series of posts into one single post. Here’s my series on the mathematical magic show that I’ll perform from time to time.

Part 1: Introduction.

Part 2a, 2b, and 2c: The 1089 trick.

Part 3a, 3b, and 3c: A geometric magic trick (see also here).

Part 4a, 4b, 4c, and 4d: A trick using binary numbers.

Part 5a, 5b, 5c, 5d: Predicting a digit that’s been erased from a number.

Part 6: Finale.

Part 7: The Fitch-Cheney 5-card trick.

Part 8a, 8b, 8c: A trick using Pascal’s triangle.

 

Stump the Prof: An Activity for Calculus I

After finishing the Product, Quotient, and Chain Rules in my calculus class, I’d tell my class the following: “Next time, we’re going to play Stump the Prof. Anything that you can write on the board in 15 seconds, I will differentiate. Anything. I don’t care how hard it looks, I’ll differentiate it (if it has a derivative). So do your best to stump me.”

At the next lecture, I would devote the last 15-20 minutes of class time to Stump the Prof. Students absolutely loved it… their competitive juices got flowing as they tried to think of the nastiest, hairiest functions that they could write on the board in 15 seconds. And I’d differentiate them all using the rules we’d just covered.. though I never promised that I would simplify the derivatives!

Sometimes the results were quite funny. Every once in a while, a student would write some amazingly awful expression but forgot to include an x anywhere. Since the given function was a constant, the derivative of course was zero.

The worst one I ever got was something like this:

y = \csc^4(\sec^5(\csc^8(\sec^7(\csc^4(\sec^5(x)))))

Differentiating this took a good 3-4 minutes and took maybe 5 lines across the entire length of the chalkboard; I remember that my arm was sore after writing down the derivative. Naturally, some wise guy used his 15 seconds to write y = in front of my answer, asking me to find the second derivative. At that, I waved my white handkerchief and  surrendered.

The point of this exercise is to illustrate to students that differentiation is a science; there are rules to follow, and by carefully following the rules, one can find the derivative of any “standard” function.

Later on, when we hit integration, I’ll draw a contrast: differentiation is a science, but integration is a combination of both science and art.

Math and practice

Sometimes math students view repetition to practice a new skill with the disdain of Allen Iverson, the legendary point guard for the Philadelphia 76ers.

So I found a recently published essay from Math With Bad Drawings to be very, very inspiring. Here are the opening paragraphs:

I’ve always felt conflicted about repetitive practice.

On the one hand, I see how vital practice is. Musicians repeat the same piece again and again. Soccer players run drills. Chefs hone their chopping motion. Shouldn’t math students do the same: rehearse the skills that matter?

But sometimes, I backtrack. “This is just going to bore them,” I fret, scanning a textbook exercise. “I’m emphasizing the rote aspects of math at the expense of the creative ones. They’re going to forget this skill anyway, and be left only with the insidious impression that math is a jackhammer subject of tooth-grinding repetition.”

(Then I assign the exercise anyway, because class starts in five minutes and— despite my repeated petitions—the administration has denied me access to a time turner.)

These two trains of thought suffer daily collisions in my mind: repetition is dull, but repetition is necessary. This inner conflict takes for granted the idea that repetitive practice is a separate endeavor, a distinct stage of the learning process. First, you learn the concept. Second, you practice it. In this view, practice is like cleaning up after a picnic: absolutely essential, but not much fun.

But this summer, a very wise teacher showed me a path forward, a way to reconciliation.

I’m referring, of course, to a two-year-old named Leo.

I highly recommend the entire article.

Fun With Permutations and Asimov’s Three Laws of Robotics

I’m not a big fan of science fiction, but I know enough to know that Isaac Asimov was one of the great science fiction novelists of the 20th century. The following was written by him in the October 1980 issue of The Magazine of Fantasy and Science Fiction and was reprinted in his book Counting the Eons, which was published in 1983. (I’m now holding the battered and torn pages of my copy of this book; I devoured Asimov’s musings on mathematics and science when I was young.)

Robotics has become a sufficiently well development technology to warrant articles and books on its history and I have watched this in amazement, and in some disbelief, because I invented it.

No, not the technology, the word.

In October 1941, I wrote a robot story entitled “Runaround,” first published in the March 1942 issue of Astounding Science Fiction, in which I recited, for the first time, my Three Laws of Robotics. Here they are:

  1. A robot must not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey the orders give it by human beings except where those orders would conflict with the First Law.
  3. A robot must protect its own existence, except where such protection would conflict with the First or Second Laws.

Clearly, the order in which the Three Laws of Robotics matters. Shuffling the order leads to 3! = 6 possible permutations, and xkcd recently had some fun about what the consequences would be of those permutations.

Source: http://www.xkcd.com/1613/

Tennis and best 2-out-of-3 vs. best 3-out-of-5

I recently read a very interesting article on FiveThirtyEight.com regarding men’s and women’s tennis that reminded me of the following standard problem in probability.

Player X and Player Y play a series of at most n games, and a winner is declared when either Player X or Player Y wins at least n/2 games. Suppose that the chance that Player X wins is p, and suppose that the outcomes of the games are independent. Find the probability that Player Y wins if (a) n = 3, (b) n = 5.

The easiest way to solve this is to assume that all n games are played, even if that doesn’t actually happen in real life. Then, for part (a), we can use the binomial distribution to find

  • P(X = 0) = P(Y = 3) = (1-p)^3
  • P(X = 1) = P(Y = 2) = 3p(1-p)^2
  • P(X = 2) = P(Y = 1) = 3p^2(1-p)
  • P(X = 3) = P(Y = 0) = p^3

Adding the first two probabilities, the chance that Player Y wins is (1-p)^3 + 3p(1-p)^2 = (1-p)^2 (1+2p).

Similarly, for part (b),

  • P(X = 0) = P(Y = 5) = (1-p)^5
  • P(X = 1) = P(Y = 4) = 5 p (1-p)^4
  • P(X = 2) = P(Y = 3) = 10p^2 (1-p)^3
  • P(X = 3) = P(Y = 2) = 10 p^3 (1-p)^2
  • P(X = 4) = P(Y = 1) = 5 p^4 (1-p)
  • P(X = 5) = P(Y = 0) = p^5

Adding the first three probabilities, the chance that Player Y wins is (1-p)^5 + 5p(1-p)^4 + 10p^2(1-p)^3 = (1-p)^3 (1+3p+6p^2).

The graphs of (1-p)^2 (1+2p) and (1-p)^3 (1+3p+6p^2) on the interval 0.7 \le p \le 0.9 are shown below in blue and orange, respectively. The lesson is clear: if p > 0.5, then clearly the chance that Player Y wins is less than 50%. However, Player Y’s chances of upsetting Player X are greater if they play a best 2-out-of-3 series instead of a best 3-out-of-5 series.

best2outof3Remarkably, this above curve has been observed in real-life sports: namely, women’s tennis (which plays best 2 sets out of 3 — marked WTA below) and men’s tennis (which plays best 3 sets out of 5 in Grand Slams — marked ATP below). The chart indicates that when two men’s players ranked 20 places apart play each other in Grand Slams, an upset occurs about 13% of the time. However, the upset percentage is only 5% in women’s tennis. (This approximately matches the above curve near p = 0.8.)

However, in tennis tournaments that are not Grand Slams, men’s tennis players also play a matches with a maximum of 3 sets. In those tournaments, the chances of an upset are approximately equal in both men’s tennis and women’s tennis.

However, since the casual tennis fan (like me) only tunes into the Grand Slams but not other tennis matches, this fact is not widely known — which gives the misleading impression that top women’s tennis players are not as tough, skilled, etc. as men’s tennis players.

The FiveThirtyEight article argues that top women’s tennis players don’t make it to the latter stages of Grand Slam tournaments than top men’s players because of the two tournaments are held under these different rules, and that women’s tennis would be better served if their matches were also played in a best-3-out-of-5 format.