STA221H1 Lecture Notes - Lecture 22: Dependent And Independent Variables, Analysis Of Variance

• School: UTSG
• Department: Statistical Sciences
• Course: STA221H1
• Professor: Augustin Vukov

Document Summary

> # read infant mortality data le in r and save it to infant_mort for attachment. > infant_mort # change my lastname to yours for the response variable. > # fit a full model: e(y) = b0 + b1childdeaths +b2hsdrop + b3lowbw + b4teenbirths + > full. model|t|) (intercept) 1. 63168 0. 91239 1. 788 0. 0806 . Residual standard error: 0. 752 on 44 degrees of freedom. F-statistic: 21. 83 on 5 and 44 df, p-value: 6. 307e-11. > # fit a reduced model: e(y) = b0 + b1childdeaths + b3lowbw. Call: lm(formula = aslemand_infantmort ~ childdeaths + lowbw) Error t value pr(>|t|) (intercept) 1. 43612 0. 71027 2. 022 0. 048898 * Signif. codes: 0 ***" 0. 001 **" 0. 01 *" 0. 05 . " 0. 1 " 1.