Using R for Introductory Statistics
by John Verzani
Publisher: Chapman & Hall/CRC 2004
ISBN/ASIN: 1584884509
ISBN-13: 9781584884507
Number of pages: 114
Description:
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.
Download or read it online for free here:
Download link
(2.1MB, PDF)
Similar books
Dynamic Programming and Bayesian Inference: Concepts and Applicationsby Mohammad Saber Fallah Nezhad (ed.) - InTech
Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. The purpose of this volume is to provide some applications of Bayesian optimization and dynamic programming.
(8443 views)
Introduction to Statistical Thoughtby Michael Lavine
Upper undergraduate or graduate book in statistical thinking for students with a background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how to put those ideas into practice.
(16602 views)
Lies, Damned Lies, or Statistics: How to Tell the Truth with Statisticsby 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.
(4975 views)
Bayesian Networks: Advances and Novel Applicationsby Douglas McNair (ed.) - IntechOpen
Bayesian networks have recently experienced increased interest and diverse applications in numerous areas, including economics, risk analysis, assets and liabilities management, AI and robotics, transportation systems planning and optimization, etc.
(5072 views)