This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied.

This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, GSK, TfL, the NHS, Shell, Unilever, and W.H.S. Although the emphasis in this guide is on applications of IBM SPSS Statistics, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the package; therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum.

This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied.

Designed to help students analyze and interpret research data using IBM SPSS, this user-friendly book, written in easy-to-understand language, shows readers how to choose the appropriate statistic based on the design, and to interpret outputs appropriately. The authors prepare readers for all of the steps in the research process: design, entering and checking data, testing assumptions, assessing reliability and validity, computing descriptive and inferential parametric and nonparametric statistics, and writing about outputs. Dialog windows and SPSS syntax, along with the output, are provided. Three realistic data sets, available on the Internet, are used to solve the chapter problems. The new edition features: Updated to IBM SPSS version 20 but the book can also be used with older and newer versions of SPSS. A new chapter (7) including an introduction to Cronbach’s alpha and factor analysis. Updated Web Resources with PowerPoint slides, additional activities/suggestions, and the answers to even-numbered interpretation questions for the instructors, and chapter study guides and outlines and extra SPSS problems for the students. The web resource is located www.routledge.com/9781848729827 . Students, instructors, and individual purchasers can access the data files to accompany the book at www.routledge.com/9781848729827 . IBM SPSS for Introductory Statistics, Fifth Edition provides helpful teaching tools: All of the key IBM SPSS windows needed to perform the analyses. Complete outputs with call-out boxes to highlight key points. Flowcharts and tables to help select appropriate statistics and interpret effect sizes. Interpretation sections and questions help students better understand and interpret the output. Assignments organized the way students proceed when they conduct a research project. Examples of how to write about outputs and make tables in APA format. Helpful appendices on how to get started with SPSS and write research questions. An ideal supplement for courses in either statistics, research methods, or any course in which SPSS is used, such as in departments of psychology, education, and other social and health sciences. This book is also appreciated by researchers interested in using SPSS for their data analysis.

This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS.

Intended as a supplement for intermediate statistics courses taught in departments of psychology, education, business, and other health, behavioral, and social sciences.

This practical, conceptual introduction to statistical analysis by award-winning teacher Andrew N. Christopher uses published research with inherently interesting social sciences content to help students make clear connections between statistics and real life. Using a friendly, easy-to-understand presentation, Christopher walks students through the hand calculations of key statistical tools and provides step-by-step instructions on how to run the appropriate analyses for each type of statistic in SPSS and how to interpret the output. With the premise that a conceptual grasp of statistical techniques is critical for students to truly understand why they are doing what they are doing, the author avoids overly formulaic jargon and instead focuses on when and how to use statistical techniques appropriately.