It's the text book for a prerequisite class for our Statistics graduate program. This book introduces essential theories in Statistics. If you review some calculus and algebra, you will be find go through the book and the more you read the more you get from this book. I've read it three times and tried its examples. This book is not the most difficult one in Statistics yet but if you are not a math major, you may want to try...
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The 7th edition of this textbook represents a great revision of this old favorite: a separate chapter on the normal distribution and a new chapter on Bayesian statistics. Lots of new problems too. It seems like a lot of the reviews are from bitter students... yes, a course using this text requires a lot of math, but that is the only way you can fully understand probability and statistics!
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I disagree with others on this one. The book is perhaps a little dry for non-mathematically oriented. If you are a math major this book will work out fine. Sometimes however, some of us who start out as math majors at the undergrad level will come to a point where we realize pure math is no longer our forte. I suppose that is when applied fields like engineering, economics or finance start looking more promising than mathematics...
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This is a wonderful book to introduce Probability and Statistical Inference to students with some background in calculus. The contents of the book start with summary and display of data, then gradually move to estimation, hypothesis testing, linear model and non-parametric methods. Several lists of distributions, confidence intervals and tests of hypothesis are given in the book. Many interesting examples are chosen to...
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