Introduction to Statistics
David Lane, Rice University
This text covers all the standard topics in a semester long introductory course in statistics. It is particularly well indexed and very easy to read more
This text covers all the standard topics in a semester long introductory course in statistics. It is particularly well indexed and very easy to navigate. There is comprehensive hyperlinked glossary.
The material is completely accurate. There are no errors. The terminology is standard with one exception: the book calls what most people call the interquartile range, the H-spread in a number of places. Ideally, the term "interquartile range" would be used in place of every reference to "H-spread." "Interquartile range" is simply a better, more descriptive term of the concept that it describes. It is also more commonly used nowadays.
This book came out a number of years ago, but the material is still up to date. Some more recent case studies have been added.
The writing is very clear. There are also videos for almost every section. The section on boxplots uses a lot of technical terms that I don't find are very helpful for my students (hinge, H-spread, upper adjacent value).
The text is internally consistent with one exception that I noted (the use of the synonymous words "H-spread" and "interquartile range").
The text book is brokenly into very short sections, almost to a fault. Each section is at most two pages long. However at the end of each of these sections there are a few multiple choice questions to test yourself. These questions are a very appealing feature of the text.
The organization, in particular the ordering of the topics, is rather standard with a few exceptions. Boxplots are introduced in Chapter II before the discussion of measures of center and dispersion. Most books introduce them as part of discussion of summaries of data using measure of center and dispersion. Some statistics instructors may not like the way the text lumps all of the sampling distributions in a single chapter (sampling distribution of mean, sampling distribution for the difference of means, sampling distribution of a proportion, sampling distribution of r). I have tried this approach, and I now like this approach. But it is a very challenging chapter for students.
The book's interface has no features that distracted me. Overall the text is very clean and spare, with no additional distracting visual elements.
The book contains no grammatical errors.
The book's cultural relevance comes out in the case studies. As of this writing there are 33 such case studies, and they cover a wide range of issues from health to racial, ethnic, and gender disparity.
Each chapter as a nice set of exercises with selected answers. The thirty three case studies are excellent and can be supplement with some other online case studies. An instructor's manual and PowerPoint slides can be obtained by emailing the author. There are direct links to online simulations within the text. This text is very high quality textbook in every way.
Table of Contents
2. Graphing Distributions
3. Summarizing Distributions
4. Describing Bivariate Data
6. Research Design
7. Normal Distributions
8. Advanced Graphs
9. Sampling Distributions
11. Logic of Hypothesis Testing
12. Testing Means
15. Analysis of Variance
17. Chi Square
18. Distribution-Free Tests
19. Effect Size
20. Case Studies
About the Book
Introduction to Statistics is a resource for learning and teaching introductory statistics.
About the Contributors
David Lane is an Associate Professor in the Departments of Psychology, Statistics, and Management at the Rice University.