Elementary Statistical Methods
by Christian Akrong Hesse
Publisher: ResearchGate GmbH 2011
Number of pages: 83
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. It can be used as a textbook for a first course in statistical methods in Universities and Polytechnics. Our goal is to introduce the basic theory without getting too involved in mathematical detail, and thus to enable a larger proportion of the book to be devoted to practical applications.
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by Jonathan A. Poritz - Colorado State University, Pueblo
This is a first draft of a free textbook for a one-semester, undergraduate statistics course. Contents: One-Variable Statistics - Basics; Bi-variate Statistics - Basics; Linear Regression; Probability Theory; Bringing Home the Data; Basic Inferences.
by David W. Stockburger - Missouri State University
The book for a course in multivariate statistics for first year graduate or advanced undergraduates. It is neither a mathematical treatise nor a cookbook. Instead of complicated mathematical proofs the author wrote about mathematical ideas.
by Allen B. Downey - Green Tea Press
Think Bayes is an introduction to Bayesian statistics using computational methods. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
by Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.