Statistics Using IBM SPSS
An Integrative Approach

A clear, lively and data-centric introduction to statistics with integrated SPSS (version 22) commands. Features a new chapter on research design.

Sharon Lawner Weinberg (Author), Sarah Knapp Abramowitz (Author)

9781107461222, Cambridge University Press

Paperback / softback, published 2 March 2016

592 pages, 196 b/w illus. 100 tables 417 exercises
25.5 x 20.5 x 3 cm, 1.24 kg

'This book covers a broad range of topics in introductory statistics, employing a hands-on, problem-based approach. The latest edition expands an already long list of topics to include bootstrap techniques and experimental design considerations. By providing detailed, worked-through examples based on real data and substantive research questions, the authors guide the student through the data analysis process from beginning to end. However, this is no 'cookbook' - each section builds on the concepts and techniques established previously, and the reader is encouraged to explore the nuances involved in effective statistical analysis. What is particularly unique about the authors' exposition is that it can be read on many levels; this book will serve well as a course textbook or as a handy reference for the applied researcher.' Marc A. Scott, New York University

Written in a clear and lively tone, Statistics Using IBM SPSS provides a data-centric approach to statistics with integrated SPSS (version 22) commands, ensuring that students gain both a deep conceptual understanding of statistics and practical facility with the leading statistical software package. With one hundred worked examples, the textbook guides students through statistical practice using real data and avoids complicated mathematics. Numerous end-of-chapter exercises allow students to apply and test their understanding of chapter topics, with detailed answers available online. The third edition has been updated throughout and includes a new chapter on research design, new topics (including weighted mean, resampling with the bootstrap, the role of the syntax file in workflow management, and regression to the mean) and new examples and exercises. Student learning is supported by a rich suite of online resources, including answers to end-of-chapter exercises, real data sets, PowerPoint slides, and a test bank.

1. Introduction
2. Examining univariate distributions
3. Measures of location, spread, and skewness
4. Re-expressing variables
5. Exploring relationships between two variables
6. Simple linear regression
7. Probability fundamentals
8. Theoretical probability models
9. The role of sampling in inferential statistics
10. Inferences involving the mean of a single population when ? is known
11. Inferences involving the mean when ? is not known: one- and two-sample designs
12. Research design: introduction and overview
13. One-way analysis of variance
14. Two-way analysis of variance
15. Correlation and simple regression as inferential techniques
16. An introduction to multiple regression
17. Nonparametric methods.

Subject Areas: Probability & statistics [PBT], Social research & statistics [JHBC], Research methods: general [GPS]