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 This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures. Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics.

 The updated Second Edition of Herschel Knapp’s friendly and practical introduction to statistics shows students how to properly select, process, and interpret statistics without heavy emphasis on theory, formula derivations, or abstract mathematical concepts. Each chapter is structured to answer questions that students most want answered: What statistical test should I use for this situation? How do I set up the data? How do I run the test? How do I interpret and document the results? Online tutorial videos, examples, screenshots, and intuitive illustrations help students "get the story" from their data as they learn by doing, completing practice exercises at the end of each chapter using prepared downloadable data sets.

 How to Use SPSS® is designed with the novice computer user in mind and for people who have no previous experience of using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 250 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS® the definitive, field-tested resource for learning SPSS. New to this edition: Fully updated to SPSS 24 and IBM SPSS Statistics Cloud New chapter on ANOVA New material on inter-rater reliability New material on syntax Additional coverage of data entry and management

 Applied statistics text updated to be consistent with SPSS version 15, ideal for classroom use or self study.

 Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis.

 The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.

 This supplementary book for the social, behavioral, and health sciences helps readers with no prior knowledge of IBM® SPSS® Statistics, statistics, or mathematics learn the basics of SPSS. Designed to reduce fear and build confidence, Basic SPSS Tutorial by Manfred te Grotenhuis and Anneke Matthijssen guides readers through point-and-click sequences using clear examples from real scientific research and invites them to replicate the findings. Relevant outcomes are provided for reference, and exercises at the end of Chapters 2 – 5 provide additional practice. After reading the book and using the program, readers will come away with a basic knowledge of the most commonly used procedures in statistics.

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

 Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements. The book looks at the process of empirical research into the following seven stages: Formulation of the problem Stipulation of the precision requirements Selecting the statistical model for the planning and analysis The (optimal) design of the experiment or survey Performing the experiment or the survey Statistical analysis of the observed results Interpretation of the results.

 There is a growing trend these days to use statistical methods to comprehend and explain various situations and phenomena in different disciplines. Managers, social scientists and practicing researchers are increasingly collecting information and applying scientific methods to analyze the data. The ability to use statistical methods and tools becomes a crucial skill for the success of such efforts. This book is designed to assist students, managers, academics and researchers in solving statistical problems using SPSS and to help them understand how they can apply various statistical tools for their own research problems. SPSS is a very powerful and user friendly computer package for data analyses. It can take data from most other file types and generate tables, charts, plots, and descriptive statistics, and conduct complex statistical analyses. After providing a brief overview of SPSS and basic statistical concepts, the book covers: - Descriptive statistics - t-tests, chi-square tests and ANOVA - Correlation analysis - Multiple and logistics regression - Factor analysis and testing scale reliability - Advanced data handling Illustrated with simple, practical problems, and screen shots, this book outlines the steps for solving statistical problems using SPSS. Although the illustrations are based on version 16.0 of SPSS, users of the earlier versions will find the book equally useful and relevant. Written in a reader-friendly, non-technical style, this book will serve as a companion volume to any statistics textbook.

 For those who have a basic understanding of statistics and want to learn SPSS on their own, Using IBM SPSS Statistics, Second Edition by James O. Aldrich and James B. Cunningham is a concise, practical guide that can be used in conjunction with another text or as a self-instructional resource. With the assistance of ample screenshots, bullet points, and callouts, readers master SPSS by inputting and analyzing their own data, rather than simply opening existing databases. The Second Edition introduces advanced concepts such as Logistic Regression, Principal Components Factor Analysis, and more complex graphing methods. This edition is compatible with IBM SPSS versions through 23.