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I had never heard of Casella & Berger (but I'm the salty guy on the data structures threads going on about how great TAOCP is). I looked it up on Amazon and it looks interesting and like exactly what I've been looking for, but there's no "look inside this book" or even a table of contents on there. Before I pick it up, how much math background would I probably need to be able to penetrate it? I'm up on calculus and linear algebra, but I only took one statistics course as an undergrad 25 years ago.



there's a pdf floating around - for me it's the first hit when i search casella berger on google

>I'm up on calculus and linear algebra, but I only took one statistics course as an undergrad 25 years ago.

it is a serious graduate math stats book but i personally don't consider it a graduate math book (because it does not use measure theory). it is proof focused because it's used for foundational grad stats classes (i.e. prep for quals) but the proofs aren't that hard to follow (if you've had a good calculus class [epsilon-delta definition of limits]).

some of the exercises are brutal algebraically though. good things there's a solutions manual floating around :)


> some of the exercises are brutal algebraically though

This is definitely true, and I wouldn't recommend this book to anyone unless they considered this a feature. For me, it was/is a feature, because I suck at algebra, and this is helpful.




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