Name: Probability and statistics
ISBN: 9781292025049

Probability and statistics

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a new chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), expanded coverage of residual analysis in linear models, and more examples using real data.

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trextrexNov 2015

One of the books that I personally found easy to read with good exercises is Probability and Statistics by Morris H. DeGroot, Mark J. Schervish

http://www.amazon.com/Probability-Statistics-Edition-Morris-...

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daniel-levinNov 2014

>> 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

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DeathArrowApr 2020

Those books cover a part of topics I've studied at the University:

The Art of Computer Programming by Donald Knuth

Introduction to Algorithms by Thomas Cormen

An Introduction to Formal Languages and Automata by Peter Linz

Probability and Statistics by by Morris H. DeGroot

Operating Systems: Internals and Design Principles by William Stallings

Understanding Cryptography by Christof Paar

Database Systems: Fundamentals of Design, Implementations and Management by by Peter Rob

Principles of Concurrent and Distributed Programming: Algorithms and Models by M. Ben-Ari

Introduction to Graph Theory by Richard Trudeau

Advanced Data Structures by Peter Brass

Ones and Zeros: Understanding Boolean Algebra, Digital Circuits, and the Logic of Sets by John Gregg

An Introduction to Algebraic Structures by Joseph Landin

Theory of Computation by S.N. Sivanandam

You can always find more on https://cstheory.stackexchange.com/ or on some universities websites.

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nikkevMay 2016

When I was taking a class in Statistical Inference, we used a combination of Statistical Inference (Casella and Berger), Introduction to Mathematical Statistics (Hogg and Craig) and Probability and Statistics (Degroot and Schervish). If you're still interested in learning about Fisher Information and the Cramer-Rao Lower Bound, you can refer to pages 514 - 521 of Probability and Statistics 8th Ed. It has a number of proofs which you can skip if you're not interested but it also provides a number of examples using different distributions to calculate both the Fisher Information and the Cramer-Rao Lower Bound.

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