This is a nice feature from Bloomberg about Ivana Seric, a data scientist who uses statistical analysis for the Philadelphia 76ers.

This is a nice feature from Bloomberg about Ivana Seric, a data scientist who uses statistical analysis for the Philadelphia 76ers.

*Posted by John Quintanilla on May 25, 2020*

https://meangreenmath.com/2020/05/25/the-nba-data-scientist/

*Posted by John Quintanilla on May 22, 2020*

https://meangreenmath.com/2020/05/22/how-to-use-facebook-emoji-to-respond-to-a-mathematical-proof/

Sadly, the snakes fail the vertical line test.

Source: https://www.facebook.com/photo.php?fbid=2275159199164147&set=gm.500736803735509&type=3&theater

*Posted by John Quintanilla on May 18, 2020*

https://meangreenmath.com/2020/05/18/snakes-on-a-plane/

News You Can Use, courtesy of Popular Mechanics: The mathematical ways to most efficiently mow your yard, by shape of yard.

https://www.popularmechanics.com/science/math/a28722621/mow-your-lawn-using-math/

*Posted by John Quintanilla on May 15, 2020*

https://meangreenmath.com/2020/05/15/how-to-mow-your-lawn-using-math/

*Posted by John Quintanilla on May 11, 2020*

https://meangreenmath.com/2020/05/11/the-mathematical-equivalent-of-sticking-a-fork-into-an-electrical-socket/

We interrupt our regular programming for this quick message to the University of North Texas College of Science Class of 2020, whose graduation we had planned to celebrate this weekend.

*Posted by John Quintanilla on May 8, 2020*

https://meangreenmath.com/2020/05/08/a-quick-message-to-the-class-of-2020/

This was a nice write-up (with some entertaining interspersed snark) of the solution of the the Wasserman-Wolf problem concerning the construction of a perfect lens (like a camera lens). Some quotes:

[L]enses are made from spherical surfaces. The problem arises when light rays outside the center of the lens or hitting at an angle can’t be focused at the desired distance in a point because of differences in refraction.

Which makes the center of the image sharper than the corners…

In a 1949 article published in the Royal Society Proceedings, Wasserman and Wolf formulated the problem—how to design a lens without spherical aberration—in an analytical way, and it has since been known as the Wasserman-Wolf problem…

The problem was solved in 2018 by doctoral students in Mexico. For those fluent in Spanish, the university press release can be found here. As an added bonus, here’s the answer:

*Posted by John Quintanilla on May 4, 2020*

https://meangreenmath.com/2020/05/04/goodbye-aberration-physicist-solves-2000-year-old-optical-problem/

*Posted by John Quintanilla on May 1, 2020*

https://meangreenmath.com/2020/05/01/can-i-do-something-to-help-my-grade/

A pet peeve of mine is measuring things to far too many decimal places. For example, notice that the thickness of these trash bags is 0.0009 inches (0.9 mil) but is 22.8 microns in metric. There are two mistakes:

- While the conversion factor is correct, there’s no way that the thickness is known within only 0.1 microns, or 100 nanometers. That’s significantly that a typical cell nucleus.
- Less importantly, if they rounded correctly, it should be 22.9 microns, not 22.8.

My favorite example that I’ve personally witnessed — that I wish I had a picture of — is measuring student’s perceptions of a professor’s teaching effectiveness is 13 decimal places.

This webcomic from xkcd illustrates the point both cleverly and perfectly.

Source: https://xkcd.com/2170/

*Posted by John Quintanilla on April 27, 2020*

https://meangreenmath.com/2020/04/27/significant-digits-and-useless-digits/

I recently enjoyed reading about an unanticipated failed marketing campaign of the 1980s. Here’s the money quote:

One of the most vivid arithmetic failings displayed by Americans occurred in the early 1980s, when the A&W restaurant chain released a new hamburger to rival the McDonald’s Quarter Pounder. With a third-pound of beef, the A&W burger had more meat than the Quarter Pounder; in taste tests, customers preferred A&W’s burger. And it was less expensive. A lavish A&W television and radio marketing campaign cited these benefits. Yet instead of leaping at the great value, customers snubbed it.

Only when the company held customer focus groups did it become clear why. The Third Pounder presented the American public with a test in fractions. And we failed. Misunderstanding the value of one-third, customers believed they were being overcharged. Why, they asked the researchers, should they pay the same amount for a third of a pound of meat as they did for a quarter-pound of meat at McDonald’s. The “4” in “¼,” larger than the “3” in “⅓,” led them astray.

Here’s the article: https://gizmodo.com/whats-bigger-1-3-pound-burgers-or-1-4-pound-burgers-1611118517

*Posted by John Quintanilla on April 24, 2020*

https://meangreenmath.com/2020/04/24/whats-bigger-1-3-pound-burgers-or-1-4-pound-burgers/