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I plan to do a course on statistical inference, and would like to ask if anyone could recommend any useful texts. It will include topics such as sufficiency, likelihood, Bayesian approaches (& follows on from a 1st course in distribution theory).

The ideal text would be something that is in fairly large font and uncluttered text (unlike Wackerly & Mendenhall), is organised well, explains concepts clearly, and has lots of exercises and clear, worked solutions (exercises without solutions are not of much use).

Any suggestions would be appreciated (especially as it's difficult to gauge a text without purchasing it).

Silverfish
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Matt
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    This request overlaps considerably with https://stats.stackexchange.com/questions/33197 and https://stats.stackexchange.com/questions/204736, which you might find useful. [This site search](https://stats.stackexchange.com/search?q=is%3Awiki+inference+book+score%3A5) will turn up several more related threads. – whuber Apr 24 '21 at 15:32
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    Not sure why this question is downvoted. When asking for resources that cover a topic, here statistical inference, it's perfectly reasonable to ask about coverage of a couple of areas that can crop up in the study of that topic but which not all textbooks will include (it's easy to find textbooks on inference that don't include Bayesian approaches, for example, particularly older or more introductory ones). An important aspect of asking for suitable resources is saying what prerequisites are assumed, which this question remembers to do. I think it's been asked pretty well actually. – Silverfish May 01 '21 at 20:29

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OpenIntro Statistics by Christopher D. Barr, David M. Diez, and Mine Çetinkaya-Rundel is a really good one to start with.

Igor Igor
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These are some good books for understagraduate and master level:

  1. https://www.dcpehvpm.org/E-Content/Stat/E%20L%20Lehaman.pdf
  2. https://www.cambridge.org/core/books/essentials-of-statistical-inference/7CDE4B08DD68DE7EE0B00F778FC29CCD
  3. https://books.google.co.uk/books?hl=el&lr=&id=yxZtddB_Ob0C&oi=fnd&pg=PR5&dq=Bayesian+Reasoning+and+Machine+Learning&ots=A1QLKacMxo&sig=LbvjmBK5dFmXHOcU7MpQCOmstAg#v=onepage&q=Bayesian%20Reasoning%20and%20Machine%20Learning&f=false
John Angelopoulos
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    Maybe, you could develop a little more, complete reference and by degree. Thank you! – POC Apr 24 '21 at 11:15
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    When covering Bayesian methods you'll see that a lot of the other topics (e.g., sufficiency and large sample theory) are no longer needed. I would teach Bayesian methods first, which places all the rest in proper context. So start with _Statistical Rethinking_ by Richard McElreath, 2nd edition. – Frank Harrell Apr 24 '21 at 13:17