Thus it is desirable to use a set of easily

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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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