Review of “Conversations On Data Science” by Roger D. Peng and Hilary Parker

“Conversations On Data Science” is a book different than others. It is a transcript of podcast episodes and host conversations. I was sure that it was going to be interesting even for people who did not listen to those podcast episodes. Let’s say that I was wrong.

I have a hard time bashing books mostly because I appreciate the author’s effort and their will to share knowledge. In this case, it is even more difficult because it means that I wouldn’t like the podcast either. Unfortunately, that seems to be the case.

In the whole book, there is only one chapter I enjoyed reading: “Analyses that seem easy.” That chapter is about power and sample size calculations. I enjoyed it because this is precisely the problem I struggle with. I am never sure whether I have calculated it correctly. If Hilary and Roger have similar issues, maybe I should not feel bad about myself ;)

I really can’t tell what is wrong about this book. Maybe the set of discussed problems is not attractive. Perhaps, only people who listen to that podcast were the target group, so I should not even expect to enjoy it. Let’s assume that it is a problem. I am not a listener of the “Not So Standard Deviations” podcast, and that is why I don’t like that book.

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Bartosz Mikulski

Bartosz Mikulski

  • Data/MLOps engineer by day
  • DevRel/copywriter by night
  • Python and data engineering trainer
  • Conference speaker
  • Contributed a chapter to the book "97 Things Every Data Engineer Should Know"
  • Twitter: @mikulskibartosz
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