Some friends and I (statistics grad students) would like to work through a good regression book. We're looking for

  • single and multiple linear regression
  • logistic regression
  • model selection
  • diagnostics
  • splines
  • penalized methods
  • classifiers, trees

Can anyone recommend a book (or books) that cover these topics?

  • 2
    $\begingroup$ It doesn't appear that you're actually asking for a regression text, per se. But, the "standard" beginning graduate text that is going to cover all of those topics is ESL. Of course, covering so many topics necessarily means that either (a) the book is huge or (b) there is some lack of depth for each topic. ESL takes the latter approach (for the most part). $\endgroup$
    – cardinal
    Jan 25, 2013 at 0:34
  • 2
    $\begingroup$ Maybe some econometric texts? Graduate level are Greene "econometric analysis", Hayashi "econometrics" and very good for time series is Hamilton "time series analysis". They are quite complete though Greene and Hayashi more or less limit themselves to discrete time. $\endgroup$
    – IMA
    Jan 25, 2013 at 9:38
  • 2
    $\begingroup$ Frank Harrell's *Regression Modeling Strategies" might be a good choice for an applied perspective. $\endgroup$
    – Charlie
    Jan 25, 2013 at 15:48
  • $\begingroup$ @IMA Hayashi is imo the best graduate econometrics book in existence. Good thinking. $\endgroup$
    – JohnK
    Jun 6, 2014 at 14:33
  • $\begingroup$ Here's a similar thread on Wakefield's book. It seems like you have plenty of options, but that's another good one. stats.stackexchange.com/questions/86057/… $\endgroup$ Mar 7, 2021 at 17:24

1 Answer 1


I believe Graham Cookson's answer to a similar question would be of assistance. Basically, he recommends Gelman and Hill's Data Analysis Using Regression and Multilevel/Hierarchical Models. According to Mr. Cookson, the book "covers basic regression, multilevel regression, and Bayesian methods in a clear and intuitive way" and "would be good for any scientist with a basic background in statistics".


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