Segment 19. The Chi Square Statistic

From Computational Statistics Course Wiki
Revision as of 14:37, 22 April 2016 by Bill Press (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

Watch this segment

(Don't worry, what you see statically below is not the beginning of the segment. Press the play button to start at the beginning.)

{{#widget:Iframe |url= |width=800 |height=625 |border=0 }}

The direct YouTube link is

Links to the slides: PDF file or PowerPoint file


To Calculate

1. Prove the assertion on lecture slide 5, namely that, for a multivariate normal distribution, the quantity , where is a random draw from the multivariate normal, is distributed.

To Think About

1. Why are we so interested in t-values? Why do we square them?

2. Suppose you measure a bunch of quantities , each of which is measured with a measurement accuracy and has a theoretically expected value . Describe in detail how you might use a chi-square test statistic as a p-value test to see if your theory is viable? Should your test be 1 or 2 tailed?

Class Exercise

Class Exercise

Data file: Media:mv_chi.txt