Unformatted text preview: p (cm), Thigh (cm),
Knee(cm), Ankle (cm), Biceps (cm), Forearm (cm), Wrist
(cm), were measured on 252 men.
• A multiple linear regression model can be built based on this data and then used for prediction of future observations:
13 ˆ
Y = β0 + ˆ
βk Xk .
k =1 • Do we need all 13 variables to predict Y or a subset would suﬃce?
2 Source of data: lib.stat.cmu.edu/datasets/ Questions to Be Answered • How to estimate the regression function?
• How good are the regression estimates?
• How reliable are the predictions?
• Does the model ﬁt the data? Do model assumptions hold?
• How to choose X variables? How to choose between competing models? How to validate a model? (Part III) Regression and Causality
• Regression analysis by itself does not imply casual...
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This document was uploaded on 03/15/2014 for the course STATS 108 at UC Davis.
 Spring '08
 Hsieh,F
 Linear Regression, Regression Analysis

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