Using R for Introductory Statistics
by John Verzani
Publisher: Chapman & Hall/CRC 2004
Number of pages: 114
The author presents a self-contained treatment of statistical topics and the intricacies of the R software. The book treats exploratory data analysis with more attention than is typical, includes a chapter on simulation, and provides a unified approach to linear models. This text lays the foundation for further study and development in statistics using R.
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by James E. Gentle - George Mason University
This document is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations.
by Philip B. Stark - University of California, Berkeley
This text was written for an introductory class in Statistics for students in Business, Economics, or Social Science. This is the first and last class in Statistics. It also covers logic and reasoning at a level suitable for a general course.
by Thomas Hill, Paul Lewicki - StatSoft, Inc.
A comprehensive statistics textbook for both beginners and advanced analysts. It presents analytic approaches and statistical methods used in science, business, industry, and data mining, written for the real-life practitioner of these methods.
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.