An EasyGuide to Experimental Design and SPSS is a handbook that provides clear and concise guidance for research methods students faced with the many decisions involved in developing the most appropriate strategy to test a hypothesis. By presenting an integrated approach to the choice of design and statistical analysis this handbook helps students connect the choice of experimental design with the choice of an appropriate statistical test for data analyses. The EasyGuide also presents the exact steps to analyze data in SPSS, including ample screenshots. The authors provide a how-to for interpreting the output from SPSS analyses, and they help students format the relevant SPSS output into an APA-style results section.
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 is the first book to demonstrate how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Version 18. The authors tap the power of SPSS''s Mixed Models routine to provide an elegant and accessible approach to these models. Readers who have learned statistics using this software will no longer have to adapt to a new program to conduct quality multilevel and longitudinal analyses. Annotated screen shots with all of the key output provide readers with a step-by-step understanding of each technique as they are shown how to navigate through the program. Diagnostic tools, data management issues, and related graphics are introduced throughout.
This textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes--all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book.
Completely up to date, the no-nonsense A SIMPLE GUIDE TO IBM SPSS: FOR VERSION 22.0, Thirteenth Edition, equips you with everything you need to know to get started with the newest version of SPSS® for Windows®. The guide's straightforward style frees learners to concentrate on learning basic statistical concepts, while still developing familiarity with SPSS®. Step-by-step instruction quickly gets users up to speed, enabling them to begin using SPSS® to conduct statistical analyses.
This book distinguishes itself from other SPSS resources through its unique integration of the research process (including design) andthe use and interpretation of the statistics. Designed to help students analyze and interpret research data, the authors demonstrate how to: choose the appropriate statistic based on the research design, interpret SPSS output, and write about the output in a research paper. The authors describe the use and interpretation of these statistics in a user-friendly, non-technical language. The book prepares students for all of the steps in the research process, from design and data collection, to writing about the results. The new edition features SPSS 14.0 for Windows, but can also be used with older and newer versions.
Statistical Analysis "In Focus" supports users of Gregory J. Privitera's Statistics for the Behavioral Sciences, Third Edition who work with a statistical program other than SPSS or Excel. Three standalone parts, each dedicated to R, SAS, and Stata, serve as step-by-step guides for completing the "In Focus" exercises in Privitera's core text. A conversational writing style along with "To The Student" introductions allow students to familiarize themselves and become more comfortable with each program prior to making computations. Additionally, General Instruction Guidebook (GIG) sections for R, SAS, and Stata provide standardized how-to instructions for using each program, making the book a valuable reference for students beyond their studies. Bundle and Save Bundle the guide with the core text, Statistics for the Behavioral Sciences, Third Edition, for only $5 more! Order using bundle ISBN 978-1-5443-3027-3.
This supplementary text is designed as a manual for SPSS use for social statistics and research methods classes and is an excellent companion to any undergraduate statistics or research methods textbook. It will also serve as a useful reference for those learning to use the SPSS software for the first time.