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tests the null hypotheis that slope = 0.
HO: slope (b)= 0 
simple linear regression


assumptions for hypothesis testing in regression analysis

RESIDUALS must be
1.uncorrelated with one another 2. normally distributed 3. equal standard deviations 

allows you to evaluate the joint and the independent effects of each of several predictor (indepenent) variables

multiple linear regression


tests the HO: bi =0

multiple linear regression


outcomes are continuous

simple and multiple regressoin


outcome measures is dichoomous

logistic regression


pros of simple linear regression

r2


if r2 high then beta is...

significant


cons of multiple linear regression

no r2


pros of logistic regression

covariate analysis


assumptions of logistic regression

independece between subjects
