All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman (Author).WINNER OF THE 2005 DEGROOT PRIZE! This e book is for individuals who wish to be taught probability and statistics quickly. It brings together most of the most important concepts in fashionable statistics in one place. The e book is appropriate for college kids and researchers in statistics, computer science, knowledge mining and machine learning. This guide covers a much wider range of subjects than a typical introductory text on mathematical statistics. It contains modern topics like nonparametric curve estimation, bootstrapping and classification, subjects which might be often relegated to comply with-up courses. The reader is assumed to know calculus and a bit linear algebra. No previous data of likelihood and statistics is required. The textual content can be used at the advanced undergraduate and graduate level.
This book provides a survey of many trendy statistical methods akin to bootstrapping and fashionable classification methods, in addition to presenting the fundamentals of inferential theory. The e book seems to be geared toward an audience familiar with arithmetic, however more interested in a basic overview of methods than rigor and restrict theorems. As such, it presents transient and readable introductions to topics akin to help vector machines, kernel estimation and Markov Chain Monte Carlo Methods that normally only seem in more specialized literature. On the entire I found it a really useful and readable text. A minor criticism is that there are a fair variety of typographical errors, particularly in equations within the later chapters; presumably this will probably be fastened in subsequent editions.
This can be a good overview of primary matters in statistics. The book is not long, but the subjects are chosen well. For example, the third chapter on statistical inference is on bootstrapping. Bayesian statistics, causal inference, graphs, non-parametric statistics, and MCMC strategies are all worthy topics which Wasserman covers but are sometimes omitted in different introductory texts.
I like this e-book significantly better than Casella and Berger---it is clearer and the topics are chosen better. But like Casella and Berger, it's meant for somebody already very accustomed to math (don't buy this guide if you happen to've only taken 3 math classes).
Excellent ebook but particularly should you're already acquainted with basic stats 101 and need an excessive stage understanding of the place to go from there. There are many references after each chapter to lookup for larger depth. The writer builds instinct rapidly and the ebook is well organized for easy skimming and re-read factors of interest. This can be close to my desk for years. Very sensible!
All of Statistics: A Concise Course in Statistical Inference
Larry Wasserman (Author)
461 pages
Springer (December 4, 2003)
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