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.
Comments
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
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.