New York: Routledge, 2013. — 521 p.
This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. A conceptual approach, built around common issues and problems rather than statistical techniques, allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Wherever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following.
Conceptual Focus – The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures.
Problems and Cases – Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output.
Continuity of Examples – A master data set containing nearly all of the data used in the book’s examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text.
Companion Website – A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises.
Field Tested – The manuscript has been field tested for three years at two leading institutions.
Introductory Statistics: A Conceptual Approach Using R
Copyright
List of Illustrations
Introduction and Background
Descriptive Statistics
Describing Quantitative Data with Frequency Distributions
Describing Quantitative Data: Summary Statistics
Describing Categorical Data: Frequency Distributions, Graphics, and Summary Statistics
Describing the Position of a Case within a Set of Scores
Describing the Relationship between Two Quantitative Variables: Correlation
Describing the Relationship between Two Quantitative Variables: Regression
The Fundamentals of Statistical Inference
The Essentials of Probability
Probability and Sampling Distributions
The Normal Distribution
Statistical Inference
The Basics of Statistical Inference: Tests of Location
Other One-Sample Tests for Location
More One-Sample Tests
Two-Sample Tests of Location
Other Two-Sample Tests: Variability and Relationships
k-Sample Tests
Tests on Location: Analysis of Variance and Other Selected Procedures
Multiple Comparison Procedures
Looking Back … and Beyond
Appendix A—Statistical Tables
Appendix B—An Introduction to R
Subject Index
Author Index