STAT 2509 Study Guide - Total Variation, Bias Of An Estimator, Normal Distribution
Document Summary
Estimated model using sample values: ( ) y is the outcome (response) variable x is the explanatory variable. 5 assumptions of the slr model: l linear - the relationship between x and y is linear. Validated by checking scatter plot of x vs y: i independence - x-values are independent of each other so that y and values are. Independently distributed with means ( ) and ( ) x-values are observed without error, for both y and . Plot y vs residuals (ei) to check violations of independence: n- normal distribution - y-values are normally distributed with n( ( ) ), and for every value of x, -values are n( ) Plot x vs residuals (ei) to check violations of constant variance z-test for population t-test. Reject h0 if t-test value < - t(n-2; /2) or t-test value > t(n-2; /2) Conclusion: at a 5% level of significance, there is evidence of a linear relationship between x and y.
