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Statistical Inference for Everyone

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Re: Statistical Inference for Everyone

#21
post #20

This book interesting because it forgoes the traditional approach of most mathematical statistics books. The preface states that it is done like this in order to avoid the "cookbook" approach taken by many statistics students. This is why it is ironic that "Bayes' Recipe" appears 15 times in this text, and on page 131 there is a five step algorithm for parameter estimation, and my favourite, oft-repeated, never expla…

"There is no mention of the CLT, MLE, method of moments estimation, biasedness of estimators, convergence in probability, how sampling distributions arise, or any of the theory of distributions that underpin all of the inferential procedures detailed in the book." Lot's of good criticisms in this thread, which I'll have to look at. This one, however, is not. :) how many intro stats book, of the traditional kind, ment…

>> how many intro stats book, of the traditional kind, mention MLE, method of moments, biased vs unbiased estimators, etc...? None that I've seen

Oh - there are quite a few. Here's a small sample (no pun intended):

- Probability and Statistical Inference by Hogg & Tanis (we used this in my stats course)

- Modern Mathematical Statistics with Applications by Devore & Berk

- Probability and Statistics by DeGroot & Schervish

Re: Statistical Inference for Everyone

#22
post #20

Earlier quoted context omitted.

"There is no mention of the CLT, MLE, method of moments estimation, biasedness of estimators, convergence in probability, how sampling distributions arise, or any of the theory of distributions that underpin all of the inferential procedures detailed in the book." Lot's of good criticisms in this thread, which I'll have to look at. This one, however, is not. :) how many intro stats book, of the traditional kind, ment…

>> how many intro stats book, of the traditional kind, mention MLE, method of moments, biased vs unbiased estimators, etc...? None that I've seen Oh - there are quite a few. Here's a small sample (no pun intended): - Probability and Statistical Inference by Hogg & Tanis (we used this in my stats course) - Modern Mathematical Statistics with Applications by Devore & Berk - Probability and Statistics by DeGroot & Scher…

Ah, yes. I concede the point. What I find interesting in all this is that the term "Introduction" is used is so many ways. When looking, for instance, for an intro bayes book you get things like Lee and Bolstad which, for some is intro. However, if you tried to teach med students or business students from that it would be a disaster.

Personally, MLE I see as just an approximation of MAP - which is superior. Biased vs unbiased also doesn't play into probability theory as logic, except as a consequence of those parameters that maximize the posterior.

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