Eric Corty’s engaging textbook is exceptionally well suited for behavioral science students studying statistical practice in their field for the first time. An award-winning master teacher, Corty speaks to students in their language, with an approachable voice that conveys the basics of collecting and understanding statistical data step by step. Examples come from the behavioral and social sciences, as well as from recognizable aspects of everyday life to help students see the relevance of what they are studying.

Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.

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 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.

For most of us, "painless" is not the word that comes to mind when we think of statistics, but author and educator Liwen Vaughan wants to change that. In this unique and useful book, Vaughan clearly explains the statistical methods used in information science research, focusing on basic logic rather than mathematical intricacies. Her emphasis is on the meaning of statistics, when and how to apply them, and how to interpret the results of statistical analysis. Through the use of real-world examples, she shows how statistics can be used to improve services, make better decisions, and conduct more effective research. Whether you are doing statistical analysis or simply need to better understand the statistics you encounter in professional literature and the media, this book will be a valuable addition to your personal toolkit. Includes more than 80 helpful figures and tables, 7 appendices, bibliography, index.

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 describes the basis, application, and interpretation of statistics, and presents a wide range of univariate and multivariate statistical methodology. The Second Edition retains the unique feature of being written from the users' perspective; it connects statistical models and methods to investigative questions and background information, and connects statistical results with interpretations in plain English. In keeping with this approach, methods are grouped by usage rather than by commonality of statistical methodology.

This market-leading text emphasizes future consumers of psychological research, uses real-world examples drawn from popular media, and develops students’ critical-thinking skills as they become systematic interrogators of information in their everyday lives.

Written in a humorous and encouraging style, this text shows how the most common statistical tools can be used to answer interesting real-world questions, presented as mysteries to be solved. Engaging research examples lead the reader through a series of six steps, from identifying a researchable problem to stating a hypothesis, identifying independent and dependent variables, and selecting and interpreting appropriate statistical tests. All techniques are demonstrated both manually and with the help of SPSS software. The book provides students and others who may need to read and interpret statistically based research with the essential knowledge and skills needed to make decisions based on data. ? Pedagogical Features Include: *Checklists of key words and formulas in every chapter. *Examples of SPSS screenshots used for analyzing data. *Cautionary notes plus "Putting It All Together" section recaps. *End-of-chapter self-quizzes (with full answers and explanations). *Glossary of terms.

Interpreting Basic Statistics gives students valuable practice in interpreting statistical reporting as it actually appears in peer-reviewed journals. New to the eighth edition: A broader array of basic statistical concepts is covered, especially to better reflect the New Statistics. Journal excerpts have been updated to reflect current styles in statistical reporting. A stronger emphasis on data visualizations has been added. The statistical exercises have been re-organized into units to facilitate ease of use and understanding. About this book Each of the 64 exercises gives a brief excerpt of statistical reporting from a published research article, and begins with guidelines for interpreting the statistics in the excerpt. The questions on the excerpts promote learning by requiring students to interpret information in tables and figures, perform simple calculations to further their interpretations, critique data-reporting techniques, and evaluate procedures used to collect data. Each exercise covers a limited number of statistics, making it easy to coordinate the exercises with lectures and a main textbook. The questions in each exercise are divided into two parts: (1) Factual Questions and (2) Questions for Discussion. The factual questions require careful reading for details, while the discussion questions show that interpreting statistics is more than a mathematical exercise. These questions require students to apply good judgment as well as statistical reasoning in arriving at appropriate interpretations.