Statistics Done Wrong
by Alex Reinhart
Publisher: refsmmat.com 2013
Statistics Done Wrong is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. It assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.
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by Keijo Ruohonen - Tampere University of Technology
Table of contents: Fundamental sampling distributions and data descriptions; One- and two-sample estimation; Tests of hypotheses; X2-tests; Maximum likelihood estimation; Multiple linear regression; Nonparametric statistics; Stochastic simulation.
by Brian S Blais - Save The Broccoli Publishing
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester.
by Irving W. Burr - McGraw-Hill
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.
by Stan Brown - BrownMath.com
This book is an alternative to the usual textbooks for a one-semester course in statistics. The author tried to make statistics approachable to anyone with high-school math, but it's still a technical subject. There is very little use of formulas.