April 2nd notes for QMB

April 2nd notes for QMB - All points not on the line are...

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April 2 nd notes for QMB *Chi square test of independence - used for 2 categorical variables Null hypothesis (Ho): the 2 categorical variables are independent Alternative hypothesis (Ha): 2 categorical variables are dependent Example: Ho: Smoking and Cancer are independent Ha: Smoking and Cancer are dependent Reject Ho if P-Value is < .05 *Regression Analysis- goes beyond correlation analysis 2 obejectives: 1. Prediction 2. To test for significance of the independent variables Chapter 15 multicollinearily – deals with number (2) objectives Simple linear regression Y=Beta(0)+Beta(1)X+e Beta(0) contant term or Y intercepet Beta(1) is the slope E- is the error Y is the dependent variable X is the independent variable
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Unformatted text preview: All points not on the line are errors ±erm – Method of least squares E squared= (Y-Beta0-Beta1X) Sum of E squared= to the sum of (y-Beta0-Beta1x) squared Multple Linear regression This is the case where we have one dependent variable (y) and two or more (say 4) independent variables (x1,x2,x3,x4) The model: Y=Beta(0)+Beta(1)X+ Beta(2)X+ Beta(3)X+ Beta(4)X+ e Using the method of least squares we obtain: Y{hat}=b(0)+b(1)X+ b(2)X+ b(3)X+ b(4)X 2 assump±ons for mul±ple regression: 1. The errors (e) are independent and normally distributed 2. The errors have constant variance...
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