When

Start: 03/13/2014 - 4:15pm

End : 03/13/2014 - 5:15pm

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__

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