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STAT 2004 Week 14

by: Mara DePena

STAT 2004 Week 14 STAT 2004

Mara DePena
Virginia Tech
GPA 3.62

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About this Document

These notes go over chi-square tests and linear regression models.
Introductory Statistics
Class Notes
Statistics, Chi-square, t-test, Best, fit, Linear, regression
25 ?




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This 1 page Class Notes was uploaded by Mara DePena on Sunday May 1, 2016. The Class Notes belongs to STAT 2004 at Virginia Polytechnic Institute and State University taught by Metzger in Spring 2016. Since its upload, it has received 17 views. For similar materials see Introductory Statistics in Statistics at Virginia Polytechnic Institute and State University.

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Date Created: 05/01/16
STAT 2004 WEEK 14 REVIEW: T-test  Use a T-test when sigma is unknown.  Use cutoffs to test, not p-values. HYPOTHESIS TESTING RATIONALE  Make an assumption. Is what you observed likely or unlikely?  Compare what you observe to what you expect. CHI-SQUARE TEST  How different is what we observed from what we expected? 2  For each category, calculate (observed−expected) . Add these values expected together for the chi-square value.  The degrees of freedom for a chi-square value is the number of categories minus 1. o Look up the actual chi-square value on the table. o Is the chi-square value you calculated larger than the value on the table? If so, reject the null. If not, fail to reject the null. BASICS OF LINEAR REGRESSION  Create an equation of a line that fits through data points as well as possible.  X is the independent variable while Y is the dependent variable.  Questions to ask yourself: o Are the points perfectly straight? o What is the best line? o What are the slope and y-intercept? o What’s the correlation (r)?  R is between -1 and +1.  Fit a line through the points. o Y= mx+b is changed to y= + x,w0th1 being t0e y-intercept and  1eing the slope. o  0nd  ar1 considered true parameters. Use estimates when using statistics, with the hats over them.  Residual- How far is the line from the actual point?  Best line- Minimizes sum of the residuals squared.


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