midterm_sol - MS&E 226 Small Data Question 1 Solutions for...

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MS&E 226 Solutions for In-Class Midterm Examination “Small” Data Question 1: D In leave-one-out CV, we measure the error at each training point from the model fitted on the remaining observations; i.e. we measure the error 5000 times in total. Question 2: A The mis-calibration means that the Y values in Michael’s training set will be twice as large as those in John’s. ˆ β is linear in Y and any predicted value is linear in ˆ β , so this will be twice as large also. Question 3: A Your estimator is simply ˆ Y = f ( X ) which has no bias or variance (there is still an irreducible error of τ 2 ). Question 4: B Since Alice and Bob use the same modeling approach, they will obtain the same model except with different values of ˆ β . Using the other half of the data set as a test set enables them to decide which of the two values for β they get predicts better. Still, that is a less efficient procedure to estimate β than just using the OLS solution based on the whole data set.
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