Slashdot Mirror
Ask Slashdot: Resources For Explaining Statistics For the Very First Time? (thejuliagroup.com)
theodp writes: Teaching multivariate statistics to college students, writes AnnMaria De Mars, was a piece of cake compared to her current project — making a game to teach statistics to middle school students who have never been exposed to the idea. In the interest of making a better game, De Mars asks, "Here's my question to you, oh reader people, what resources have you found useful for teaching statistics? I mean, resources you have really watched or used and thought, 'Hey, this would be great for teaching?' There is a lot of mediocre, boring stuff on the interwebz and if any of you could point me to what you think rises above the rest, I'd be super appreciative." Larry Gonick's The Cartoon Guide to Statistics is pretty amazing, but is it a little too advanced for this age group? Anyone have experience with the Khan Academy Data and Statistics offerings? Any other ideas?
Statistics is best learned using a "Hands On" approach. It is a difficult subject for middle school students. An example lesson is to ask a relevant class question and then use the class data to teach what ever the topic is.
The professors of the California Math Project have access to a variety of practices and resources for teaching middle school math.
Try these resources; the National Counsel of Teachers of Mathematics,(NCTM), the Illustrative Mathematics web site, and "The Teaching Channel". These web sites have teaching activities and resources for middle school math
https://en.wikipedia.org/wiki/How_to_Lie_with_Statistics
Seriously - if you want to teach intuition with statistical models - and why most media published statistics are horribly developed - this is the book. The principle bits you get out of the book: Correlation does not imply causation - a HUGE intuitive bit of knowledge to debunk a LOT of what the media throws out there.
You know, 99.3% of all convicted criminals, in one form or another, have eaten a tomato! (Yes, ketchup and pizza sauce count)
100% of everyone who as ever, or will eat on, will die. (Note: did not say how long it would take for them to die!)
How do your correlate your data so that it is meaning full? How do you determine causation, or not?
Secondly, how to properly random sample a set. What sort of biases can be introduced? How can they be recognized? Documented? Eliminated (or reduced)?
Where to get your numbers to play with? Everyone has already said sports (Baseball has more stats than any other sport - and they are readily available. Watch the movie Moneyball - how stats was used to transform the management of the sport - without negatively impacting the enjoyment of watching a game). Upcoming presidential election - people prefer this candidate over that one? What sort of biases?
Yes, going through the bazillion different distributions (both discrete and continuous) is still a requirement. As well as conceptual bits as standard deviation, and the area under the curve (why two, almost identical sets of numbers can provide different outcomes).
Here's a wacky one - (yes, it deals with guns)... Find an AirSoft automatic gun... Load it with 30 rounds of bbs' (same mfgr, weight, roundness, etc.) - set it up with it locked in position 50' from a target and and just let loose the entire clip. Make 30 of these - one for each student. Perfect example of a bell curve. No matter how well you controlled the experiment you still had a distribution. A lot of info you can pull from this... mean, median, mode (which will be rings!), and if there is a vector preference - you can analyse that as well (show's bias).
Regardless - make your examples fun, make them real. And make them something they can further investigate on their own.
FredInIT