Lectures on Statistics
by Robert B. Ash
Publisher: University of Illinois 2007
These notes are based on a course that the author gave at UIUC in 1996 and again in 1997. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results from basic probability that are important in statistics. Some exposure to matrix algebra is needed to cope with the multivariate normal distribution in Lecture 21, and there is a linear algebra review in Lecture 19.
Home page url
Download or read it online for free here:
(multiple PDF files)
by Barbara Illowsky, Susan Dean - Illowsky Publising
Intended for introductory statistics courses for students at two and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications rather than the theory.
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 Wolfgang K. Hardle, Leopold Simar - Springer
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
by Ivan Lowe - scientificlanguage.com
Here I present statistics for the ordinary person. Examples are taken from ordinary life. The book begins with basic concepts behind the statistics and never gets harder than simple arithmetic. The course is presented as a series of key ideas.