Lec03.Diagnostics

# Lec03.Diagnostics - Regression Diagnostics KNNL Ch 3...

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Regression Diagnostics KNNL Ch. 3 Lec03.Diagnostics Exercises.ppt Lec03.Diagnotics.ssc

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Recap Last Lecture Expected value Theoretical mean from probability distribution Objective: Minimize sum of squares Derivative with respect to parameters Relationship to Maximum Likelihood Theory Derived estimates of Intercept and it’s variance Slope and it’s variance Linear prediction and its variance New observation (associated with predictor) and its variance
Age (days) Wing Length (cm) 4 6 8 10 12 14 16 2 3 4 5 Approximate 95% Confidence Interval on Yhat as a function of Xh - - + = + = = 2 1 2 2 1 0 ) ( ) ( 1 ) ˆ ( ˆ n i i h h h h X X X X n MSE Y s X b b Y

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Age (days) Wing Length (cm) 4 6 8 10 12 14 16 2 3 4 5 Prediction of New Y? - - + + = + = = 2 1 2 ) ( 2 1 0 ) ( ) ( ) ( 1 1 ) ˆ ( ˆ n i i h new h h new h X X X X n MSE Y s X b b Y
Age (days) Wing Length (cm) 4 6 8 10 12 14 16 2 3 4 5 - - + + = = 2 1 2 ) ( 2 ) ( ) ( 1 1 ) ˆ ( n i i h new h X X X X n MSE Y s Variation in Prediction of New Y

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Regression Diagnostics Checking for validity of assumptions Model fit Model completeness Independence First i of iid Constancy of variance Second i of iid Outliers Normality
Do we have the right model?

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Lec03.Diagnostics - Regression Diagnostics KNNL Ch 3...

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