[MOSAIC-news] MOSAIC M-Cast Friday noon (Eastern; 11am Central)

Randall Pruim rpruim at calvin.edu
Fri Oct 8 10:50:07 CDT 2010

Begin forwarded message:

> From: Daniel Kaplan <kaplan at macalester.edu>
> Date: October 6, 2010 12:06:44 PM GMT-04:00
> Subject: MOSAIC M-Cast Friday noon (Eastern; 11am Central)
> Join us Friday for the next M-Cast from Project MOSAIC
> Golfballs in the Yard
> Friday Oct. 8 at 12:00 Eastern (11:00 Central, 9:00 Pacific)
> Randall Pruim from Calvin College will present a computational  
> approach to teaching the logic of hypothesis testing.  The mirthful  
> title of the M-CAST relates to a particular setting for hypothesis  
> testing, but the subject is serious and general.
> This M-CAST is a good opportunity both for statisticians and non- 
> statisticians.  In my experience, non-statisticians are surprised to  
> find out how accessible the concepts of statistical inference become  
> when they are placed in the straightforward context of random  
> sampling, rather than being wrapped up as formulas.  Modern  
> computing makes it feasible to emphasize the process of  
> sampling .... or would do so if students got used computing as an  
> integral part of their work.  And that's part of the idea of Project  
> MOSAIC: to show how statistics, modeling, computation, and calculus  
> can support one another in the early undergraduate curriculum.
> MOSAIC M-Casts are held the 2nd and 4th Friday of each month.  See  
> the upcoming M-Casts and recordings of past M-Casts on our schedule  
> page.
> You can join Friday's M-Cast using your web browser.  Follow these  
> instructions.
> Regards,
> Danny Kaplan
> Abstract for Golfballs in the Yard: One challenge in any  
> introductory statistics course is helping our students understand  
> the logic of hypothesis testing. In this M-Cast I'll demonstrate one  
> of my favorite examples for doing this. The data are a sample of  
> golfballs. The hypothesis is that the number on the ball is equally  
> likely to be a 1, 2 ,3 or 4. Using a function written in R, I allow  
> students to design their own test statistic and then produce a  
> graphical display of the sampling distribution and calculate  
> empirical p-values.

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