OpenIntro Statistics
(ONLINE)

OpenIntro Statistics 3rd Edition strives to be a complete introductory textbook of the highest caliber. Its core derives from the classic notions of statistics education and is extended by recent innovations. The textbook meets high quality standards and has been used at Princeton, Vanderbilt, UMass Amherst, and many other schools. We look forward to expanding the reach of the project and working with teachers from all colleges and schools. The chapters of this book are as follows: Introduction to data. Data structures, variables, summaries, graphics, and basicdata collection techniques. Probability (special topic). The basic principles of probability. An understandingof this chapter is not required for the main content in Chapters 3-8. Distributions of random variables. Introduction to the normal model and otherkey distributions. Foundations for inference. General ideas for statistical inference in the context ofestimating the population mean. Inference for numerical data. Inference for one or two sample means using the normal model and t distribution, and also comparisons of many means using ANOVA. Inference for categorical data. Inference for proportions using the normal and chi-square distributions, as well as simulation and randomization techniques. Introduction to linear regression. An introduction to regression with two variables.Most of this chapter could be covered after Chapter 1. Multiple and logistic regression. An introduction to multiple regression and logistic regression for an accelerated course. OpenIntro Statistics was written to allow exibility in choosing and ordering coursetopics. The material is divided into two pieces: main text and special topics. The maintext has been structured to bring statistical inference and modeling closer to the front of acourse. Special topics, labeled in the table of contents and in section titles, may be addedto a course as they arise naturally in the curriculum.

In English.