Intermediate Statistics

James Stevens’ best-selling text, Intermediate Statistics, is written for those who use, rather than develop, statistical techniques. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving the results. SAS and SPSS are an integral part of each chapter. Definitional formulas are used on small data sets to provide conceptual insight into what is being measured. The assumptions underlying each analysis are emphasized and the reader is shown how to test the critical assumptions using SPSS or SAS. Printouts with annotations from SAS or SPSS show how to process the data for each analysis. The annotations highlight what the numbers mean and how to interpret the results. Numerical, conceptual, and computer exercises enhance understanding. Answers are provided for half of the exercises. The book offers comprehensive coverage of one-way, power, and factorial analysis of variance, repeated measures analysis, simple and multiple regression, analysis of covariance, and HLM. Power analysis is an integral part of the book. A computer example of real data integrates many of the concepts. Highlights of the Third Edition include: A new chapter on hierarchical linear modeling using HLM6 Downloadable resources containing all of the book’s data sets New coverage of how to cross validate multiple regression results with SPSS and a new section on model selection (Chapter 6) More exercises in each chapter. Intended for intermediate statistics or statistics II courses taught in departments of psychology, education, business, and other social and behavioral sciences, a prerequisite of introductory statistics is required. An Instructor's Resource is available upon adoption. See www.researchmethodsarena.com .

Need to know how to build and test models based on data? Intermediate Statistics For Dummies gives you the knowledge to estimate, investigate, correlate, and congregate certain variables based on the information at hand. The techniques you’ll learn in this book are the same techniques used by professionals in medical and scientific fields. Picking up right where Statistics For Dummies left off, this straightforward, easy-to-follow book guides you beyond Central Limit Theorem and hypothesis tests and immerses you in flavors of regression, ANOVA, and nonparametric procedures. Unlike regular statistics books, this guide provides full explanations of intermediate statistical ideas; computer input dissection; an extensive number of examples, tips, strategies, and warnings; and clear, concise step-by-step procedures—all in a language you can understand. You’ll soon discover how to: Analyze data and base models off of your data Make predictions using regression Compare many means with ANOVA Test models using Chi-square Dealing with abnormal data In addition, this book includes a list of wrong statistical conclusions and common questions that professors ask using computer output. This book also adopts a nonlinear approach, making it possible to skip to the information you need without having to read previous chapters. With Intermediate Statistics For Dummies, you’ll have all the tools you need to make important decisions in all types of professional areas—from biology and engineering to business and politics!

Intermediate Statistics: A Conceptual Course is a student-friendly text for advanced undergraduate and graduate courses. It begins with an introductory chapter that reviews descriptive and inferential statistics in plain language, avoiding extensive emphasis on complex formulas. The remainder of the text covers 13 different statistical topics ranging from descriptive statistics to advanced multiple regression analysis and path analysis. Each chapter contains a description of the logic of each set of statistical tests or procedures and then introduces students to a series of data sets using SPSS, with screen captures and detailed step-by-step instructions. Students acquire an appreciation of the logic of descriptive and inferential statistics, and an understanding of which techniques are best suited to which kinds of data or research questions.

Intermediate Statistics fully integrates SAS and SPSS. The chapter on factorial ANOVA features thorough discussions of the unequal cell size case and interpreting effects in three-way designs, and an extensive computer example of real data which integrates many of the concepts. In addition, there are substantial chapters on covariance and repeated measures analysis. Special features of this second edition include: *a new chapter on multiple regression; *inclusion of SPSS for Windows 8.0 and Statview; and *Pass 6.0 for power analysis.

The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.

Book Publication Date: Dec 13, 2023. Full color. Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills.

What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp′s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics.

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.