Overview

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. Useful 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

Full Product Details

Author:   Steven R. Terrell
Publisher:   Guilford Publications
Imprint:   Guilford Press
Dimensions:   Width: 17.80cm , Height: 2.50cm , Length: 25.40cm
Weight:   0.904kg
ISBN:  

9781462503216

ISBN 10:   1462503217
Pages:   409
Publication Date:   08 May 2012
Audience:   College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Replaced By:   9781462545407
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   Awaiting stock  

Table of Contents

"Introduction: You Do Not Need to be a Statistician to Understand Statistics! A Little Background Many Students Don’t Know What They’re Getting Into A Few Simple Steps Summary Do You Understand These Key Words and Phrases? 1. Identifying a Research Problem and Stating Hypotheses Step 1: Identify a Problem That Can Be Investigated Using Inferential Statistics Step 2: State a Hypothesis about the Problem You Are Investigating Do You Understand These Key Words and Phrases? Quiz Time! 2. Identifying the Independent and Dependent Variables in a Hypothesis Step 3: Be Able to Identify the Independent Variable(s) and the Levels of the Independent Variable(s) in Your Hypothesis Step 4: Be Able to Identify and Statistically Describe the Dependent Variable(s) in Your Hypothesis Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 3. Measures of Dispersion and Measures of Relative Standing Measures of Dispersion Measures of Relative Standing Summary of the Measures of Dispersion and Measures of Relative Standing Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 4. Graphically Describing the Dependent Variable Graphical Descriptive Statistics The Normal Distribution Do You Understand These Key Words and Phrases? Quiz Time! 5. Choosing the Right Statistical Test The Very Basics How Are We Doing So Far? Estimating Population Parameters Using Confidence Intervals Predicting a Population Parameter Based on a Sample Statistic Using Confidence Intervals Testing Hypotheses about a Population Parameter Based on a Sample Statistic Testing a One-Tailed Hypothesis Testing a One-Tailed ""Less Than"" Hypothesis Summarizing What We Just Said Be Careful When Changing Your Alpha Values The Heart of Inferential Statistics Probability Values Step 5 Summary of Choosing the Right Statistical Test Do You Understand These Formulas and Symbols? Quiz Time! 6. The One-Sample t-Test Welcome to the Guinness Breweries The t Distribution Let’s Look at a Directional Hypothesis One More Time Let’s Use the Six-Step Model Summary of the One-Sample t-Test Do You Understand These Key Words and Phrases? Do You Know These Formulas? Quiz Time! 7. The Independent-Sample t-Test If We Have Samples from Two Independent Populations, How Do We Know If They Are Significantly Different from One Another? Putting the Independent-Sample t-Test to Work Summary of the Independent-Sample t-Test Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 8. The Dependent-Sample t-Test That’s Great, But How Do We Test Our Hypothesis? Independence versus Dependence Testing a Two-Tailed Hypothesis Let’s Move Forward and Use Our Six-Step Model The Case of the Unexcused Students The Case of Never Saying Never Summary of the Dependent Sample t-Test Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 9. The Analysis of Variance Understanding the ANOVA The Different Types of ANOVAs Assumptions of the ANOVA Calculating the ANOVA The Factorial ANOVA Interpreting the Interaction p Value Summary of the ANOVA Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 10. The Chi-Square Tests The One-Way Chi-Square Test The Factorial Chi-Square Test (the Chi-Square Test of Independence) Computing the Chi-Square Statistic The Chi-Square Test of Independence Computing Chi-square for the Test of Independence Post-Hoc Tests Following the Chi-Square Summary of the Chi-Square Tests Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! 11. The Correlational Procedures Understanding the Idea of Correlations Interpreting Pearson’s r A Nonparametric Correlational Procedure Linear Regression Summary of the Correlational Procedures Do You Understand These Key Words and Phrases? Do You Understand These Formulas? Quiz Time! Conclusion. Have We Accomplished What We Set Out to Do? Statistics in a New Light A Limited Set of Statistical Techniques The Use of Statistical Software Packages A Straightforward Approach Appendix A: Area Under the Normal Curve Table (Critical Values of z) Appendix B. Critical Values of t Appendix C. Critical Values of F When Alpha = .01 Appendix D. Critical Values of F When Alpha = .-05 Appendix E. Critical Values of Chi-Square Appendix F. Critical Values of F When Alpha = .10 Appendix G. Selecting the Right Statistical Test Glossary Answers to Quiz Time"

Reviews

Bravo to Terrell for creating an introduction to statistics that is friendly, conversational, and understandable. His focus on the most frequently used statistical analyses, vocabulary, and methods are absolutely what our students need. Terrell offers hundreds of authentic and timely research examples and case studies, leading readers through the research process in a supportive and interactive manner. I applaud the sections with key words, formulas to know, and self-quizzes. This is an excellent text for beginners in a quantitative research class or general introduction to research, such as our master's-level Introduction to Educational Research course. It is also useful for early-career academics writing their beginning journal articles, or for experienced faculty members to use as a terrific reference source. - Lynne Schrum, George Mason University, Virginia, USA I applaud the author for linking statistical reasoning to a problem-oriented framework and for including a discussion of how to identify a researchable problem and frame research questions. These are serious omissions in many texts. The book is well situated to inform upper-level undergraduate and graduate students pursuing practitioner-related degrees. It does a good job of laying out a framework for inquiry and aligning statistical reasoning and tools with this framework. It is written for an audience who may do some basic statistical calculations and analysis, but who primarily will be consumers of statistics and quantitative research. I will recommend this text to colleagues who teach statistics or more general research methods courses for this audience. - Tammy Kolbe, University of Connecticut, USA

Bravo to Terrell for creating an introduction to statistics that is friendly, conversational, and understandable. His focus on the most frequently used statistical analyses, vocabulary, and methods is absolutely what students need. Terrell offers hundreds of authentic and timely research examples and case studies, leading readers through the research process in a supportive and interactive manner. I applaud the sections with key words, formulas to know, and self-quizzes. This is an excellent text for beginners in a quantitative research class or general introduction to research, such as a master's-level Introduction to Educational Research course. It is also useful for early-career academics writing their beginning journal articles, or for experienced faculty members to use as a terrific reference source. --Lynne Schrum, PhD, Dean, College of Education and Human Services, West Virginia University The readability of this book is a definite plus; it will be easily accessible to advanced undergraduates and graduate students. Specialized vocabulary is defined and used in context, and concepts are clearly explained. I like how the end-of-chapter quizzes require students to integrate concepts highlighted in a given chapter with relevant information from previous chapters. The graphics visually build statistical concepts on one another--I particularly like the continued use of the sample distributions and how they are tied to use of normal curve assumptions. --Chris Ohana, PhD, Science, Mathematics, and Technology Education Program, Western Washington University I applaud the author for linking statistical reasoning to a problem-oriented framework and for including a discussion of how to identify a researchable problem and frame research questions. These are serious omissions in many texts. The book is well situated to inform upper-level undergraduate and graduate students pursuing practitioner-related degrees. It does a good job of laying out a framework for inquiry and aligning statistical reasoning and tools with this framework. It is written for an audience who may do some basic statistical calculations and analysis, but who primarily will be consumers of statistics and quantitative research. I will recommend this text to colleagues who teach statistics or more general research methods courses for this audience. --Tammy Kolbe, EdD, Center for Education Policy Analysis, Neag School of Education, University of Connecticut Terrell sees the application of statistics as useful for answering all sorts of interesting academic and real-life questions. His explanations reveal the mysteries behind inferential statistics as he describes how to think statistically. Readers will discover the connections among the hypothesis, dependent measures, selection of appropriate inferential statistical analysis procedures, and how to interpret the evidence. The detailed, step-by-step directions on how to conduct statistical tests using SPSS are a plus; Terrell teaches both theory and practice. --Dave Edyburn, PhD, Director of Research, School of Education, University of Wisconsin-Milwaukee This book uses interesting examples and demonstrations to explain every aspect of the data-analytic process, from developing a sound hypothesis and selecting the appropriate analysis to understanding what the results actually mean. It is easy to understand, surprisingly practical, and comprehensive. Most important, Terrell directly addresses the most common analysis question that I hear from my own students: 'How do I know which statistical analysis to use?' This is the kind of text that students will keep and refer back to repeatedly during subsequent courses. --Matthew K. Burns, PhD, School Psychology Program, University of Missouri-Columbia One of the best things about Terrell's book is that it makes clear just how easy and intuitive statistics is. It does a better job than other available texts of expressing the core ideas through words, rather than numbers. --W. Val Larsen, PhD, Department of Marketing, James Madison University Compared to other available introductory textbooks, Terrell's is among the easiest to read and understand. The material is presented well and I like that it is broken up into small parts. Research methods and data collection techniques are integrated effectively. --Brian L. Withrow, PhD, Department of Criminal Justice, Texas State University-San Marcos Terrell makes it clear that his goal is to decrease students' fear of statistics--and he succeeds beautifully. This is one statistics text that students will want to keep on their bookshelves rather than sell at the end of the semester. Rather than trying to cover every possible statistical procedure, Terrell wisely decided to focus on the subset of procedures that practitioners in education will be using 90% of the time. The book's practical focus on most-used statistics, as well its informal style and systematic approach, make it a unique and valuable learning tool. Instructors will love using a text that is so easy to read and understand. In addition to course use, I will recommend this book to my doctoral students who are preparing dissertation research proposals. It will help relieve their anxiety about statistical analyses and provide good, reliable information that they can readily apply. --M. D. Roblyer, PhD, Adjunct Professor of Instructional Technology and Distance Education, Nova Southeastern University The author's approach is friendly and gentle. This is clearly a textbook for students who have not studied statistics before and who may even be phobic about mathematics. The four-step checklist for a well-stated hypothesis will be helpful to students and there is an excellent discussion of sampling error. The examples are great--well chosen and well used. --Adam Thrasher, PhD, Department of Health and Human Performance, University of Houston This is the textbook I wish I had written--it's relaxed, it speaks to you, it informs you, and at times, it even entertains. --Todd D. Little, PhD, Department of Psychology, University of Kansas

Bravo to Terrell for creating an introduction to statistics that is friendly, conversational, and understandable. His focus on the most frequently used statistical analyses, vocabulary, and methods are absolutely what our students need. Terrell offers hundreds of authentic and timely research examples and case studies, leading readers through the research process in a supportive and interactive manner. I applaud the sections with key words, formulas to know, and self-quizzes. This is an excellent text for beginners in a quantitative research class or general introduction to research, such as a master's-level Introduction to Educational Research course. It is also useful for early-career academics writing their beginning journal articles, or for experienced faculty members to use as a terrific reference source. - Lynne Schrum, George Mason University, Virginia, USA I applaud the author for linking statistical reasoning to a problem-oriented framework and for including a discussion of how to identify a researchable problem and frame research questions. These are serious omissions in many texts. The book is well situated to inform upper-level undergraduate and graduate students pursuing practitioner-related degrees. It does a good job of laying out a framework for inquiry and aligning statistical reasoning and tools with this framework. It is written for an audience who may do some basic statistical calculations and analysis, but who primarily will be consumers of statistics and quantitative research. I will recommend this text to colleagues who teach statistics or more general research methods courses for this audience. - Tammy Kolbe, University of Connecticut, USA

Author Information

Steven R. Terrell, Graduate School of Computer and Information Sciences, Nova Southeastern University, Ft. Lauderdale, Florida, USA

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