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Have question about answers to 1(a ) and 1(d) #77

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Have question about answers to 1(a ) and 1(d) #77

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5 changes: 4 additions & 1 deletion ch2/answers
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1. (a) better - a more flexible approach will fit the data closer and with the
large sample size a better fit than an inflexible approach would be obtained
large sample size a better fit than an inflexible approach would be obtained.
YX add on: I would agree on "better" due to large sample size. But what is the effect of small number of predictors

(b) worse - a flexible method would overfit the small number of observations

(c) better - with more degrees of freedom, a flexible model would obtain a
better fit

(d) worse - flexible methods fit to the noise in the error terms and increase variance
YX add on: I am wondering if error term is very big, would variance/bias still be relevant. After all the MSE is dominated
by error terms already. How can we tell the difference between high flexibility model and low flexibility model?


2. (a) regression. inference. quantitative output of CEO salary based on CEO
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