This is a complete guide to statistics and SPSS for social science students. Statistics with SPSS for Social Science provides a step-by-step explanation of all the important statistical concepts, tests and procedures. It is also a guide to getting started with SPSS, and includes screenshots to illustrate explanations. With examples specific to social sciences, this text is essential for any student in this area.

Modern statistical software provides the ability to compute statistics in a timely, orderly fashion. This introductory statistics textbook presents clear explanations of basic statistical concepts and introduces students to the IBM SPSS program to demonstrate how to conduct statistical analyses via the popular point-and-click and the "syntax file" methods. The focal point is to show students how easy it is to analyse data using SPSS once they have learned the basics. Provides clear explanation of basic statistical concepts that provides the foundation for the beginner students’ statistical journey. Introduces the SPSS software program. Gives clear explanation of the purpose of specific statistical procedures (e.g., frequency distributions, measures of central tendencies, measures of variability, etc.). Avoids the conventional cookbook approach that contributes very little to students’ understanding of the rationale of how the correct results were obtained. The advantage of learning the IBM SPSS software package at the introductory class level is that most social sciences students will employ this program in their later years of study. This is because SPSS is one of the most popular of the many statistical packages currently available. Learning how to use this program at the very start not only familiarizes students with the utility of this program but also provides them with the experience to employ the program to conduct more complex analyses in their later years.

This book integrates social science research methods and the descriptions of 46 univariate, bivariate, and multivariate tests to include a description of the purpose, assumptions, example research question and hypothesis, SPSS procedure, and interpretation of SPSS output for each test. Included throughout the book are various sidebars highlighting key points, images and SPSS screenshots to assist understanding the material presented, self-test reviews at the end of each chapter, a decision tree to facilitate identification of the proper statistical test, examples of SPSS output with accompanying analysis and interpretations, links to relevant web sites, and a comprehensive glossary. Underpinning all these features is a concise, easy to understand explanation of the material.

Introduction to Statistics and SPSS in Psychology guides the reader carefully and concisely up the statistics staircase to success. Each step is supported by helpful visuals as well as advice on how to overcome problems. Interactive, lively, but never patronising, this is the complete guide to statistics that will take readers through their degree course from beginning to end. Take a step in the right direction and tackle statistics head on with this visual introduction.

This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefully placed reading questions throughout each chapter allow students to apply their knowledge right away, while in-depth activities based on current behavioral science scenarios, each with problem sets and quiz questions, give students the opportunity to assess their understanding of concepts while reading detailed explanations of more complex statistical concepts. Additional practice problems further solidify student learning. Most activities are self-correcting, so if a concept is misunderstood, this misunderstanding is corrected early in the learning process. After working through each chapter, students are far more likely to understand the material than when they only read the material.

Using a truly accessible and reader-friendly approach, this comprehensive introduction to statistics redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.