Simulations Might Mislead?

When
Start: 03/13/2014 - 4:15pm
End  : 03/13/2014 - 5:15pm

Category
Statistics/OR/Math Finance Seminar

Speaker
Anna Bargagliotti

Abstract
The Central Limit Theorem is often referred to as the most important theorem in statistics.  As such, statistics courses spend a significant amount of time teaching the theorem. Using simulations to teach the CLT is meant to provide students with sound conceptual understanding.  However, this talk will show that simulations may actually mislead.  
 
Together we will simulate sampling distributions for the sample means using various samples sizes and number of samples to show how a misunderstanding about the mean can be inadvertently introduced or reinforced through simulation. From observing the patterns in a typical series of simulated sampling distributions constructed with increasing sample sizes, we will show that it is plausible to incorrectly, but reasonably, conclude that, as the sample size, n, increases, the mean approaches the population mean. 
 
Where
Davidson Lecture room, Adams Hall, CMC

Claremont Graduate University | Claremont McKenna | Harvey Mudd | Pitzer | Pomona | Scripps
Proudly Serving Math Community at the Claremont Colleges Since 2007
Copyright © 2018 Claremont Center for the Mathematical Sciences