STAT 154 Lecture Notes - Lecture 6: Total Variation, Analysis Of Variance, Diagonal Matrix

• School: Berkeley
• Department: Statistics
• Course: STAT 154
• Professor: John Tuhao Chen

Document Summary

R multiple squared the linear sample regressions , correlation the multiple. Cy , it selecting the regression model variables with. = xp final multiple include to predictors ? in two a the. Xi regression model for takes categorical qualitative predictor value. Ii 2. 3 or at bi xii t be xzitb. Measuring the the data distance of an observation from the bulk of. Nii el ith diagonal the since and idempotent hithti hi i. Bi for the ith data unite is defined as ii. where. X is element in the design the matrix projection projection matrix is symmetric. H hii ith row of h the ith col of. Ee, his . hji hi j hi hi j t fti hitz h ji i. Residual of the t th data unit di. Yi - yi variance of di vcdi ? eitvcy-ytlei-e. tv. I xt ] y ) e ; e it c [