图书简介
Research Methods, Statistics, and Applications is designed to let students experience being a researcher by integrating research methods and statistics throughout the process. The Third Edition of this best-selling text features new examples, practical applications from across the social and behavioral sciences, and a conversational voice throughout to keep students engaged in the research process.
Preface \\ About the Authors \\ Chapter 1 • Thinking Like a Researcher \\ Learning Objectives \\ Critical Thinking \\ The Scientific Approach \\ Overview of the Research Process (a.k.a. The Scientific Method) \\ Thinking Critically About Ethics \\ The Big Picture: Proof and Progress in Science \\ Chapter Resources \\ Chapter 2 • Build a Solid Foundation for Your Study Based on Past Research \\ Learning Objectives \\ Types of Sources \\ Strategies to Identify and Find Past Research \\ Reading and Evaluating Primary Research Articles \\ Crediting Sources \\ The Big Picture: Use the Past to Inform the Present \\ Chapter Resources \\ Chapter 3 • Measuring Your Variables \\ Learning Objectives \\ Constructs and Operational Definitions \\ Four Scales of Measurement \\ Self-Report Measures \\ Behavioral and Physiological Measures \\ Archival Research \\ The Big Picture: How to Choose Measures For Your Study \\ Chapter Resources \\ Chapter 4 • The Cornerstones of Good Research: Reliability and Validity \\ Learning Objectives \\ Reliability and Validity Defined \\ Reliability and Validity of Measurement \\ Assessing Reliability of Measures \\ Assessing Validity of Measures \\ Reliability and Validity at the Study Level \\ The Big Picture: Consistency and Accuracy \\ Chapter Resources \\ Chapter 5 • Basics of Research Design: Description and Sampling \\ Learning Objectives \\ When is a Descriptive Study Appropriate? \\ Validity in Descriptive Studies \\ Defining the Population and Obtaining a Sample \\ Probability Sampling \\ Nonprobability Sampling \\ The Big Picture: Choosing a Sampling Method \\ Chapter Resources \\ Chapter 6 • Describing Your Sample \\ Learning Objectives \\ Ethical and Practical Issues in Describing Your Sample \\ Descriptive Statistics \\ Choosing the Appropriate Descriptive Statistics \\ Comparing Interval/Ratio Scores with z Scores and Percentiles \\ The Big Picture: Know Your Data and Your Sample \\ Chapter Resources \\ Chapter 7 • Beyond Descriptives: Making Inferences Based On Your Sample \\ Learning Objectives \\ Inferential Statistics \\ Hypothesis Testing \\ Errors in Hypothesis Testing \\ Effect Size, Confidence Intervals, and Practical Significance \\ The Big Picture: Making Sense of Results \\ Chapter Resources \\ Chapter 8 • Comparing Your Sample to a Known or Expected Score \\ Learning Objectives \\ Choosing the Appropriate Test \\ One-Sample t Tests \\ Calculating an Effect Size \\ Calculating a Confidence Interval \\ The Big Picture: Examining One Variable at a Time \\ Chapter Resources \\ Chapter 9 • Examining Relationships Among Your Variables: Correlational Design \\ Learning Objectives \\ Correlational Design \\ Basic Statistics to Evaluate Correlational Research \\ Regression \\ The Big Picture: Correlational Designs Versus Correlational Analyses \\ Chapter Resources \\ Chapter 10 • Examining Causality \\ Learning Objectives \\ Testing Cause and Effect \\ Eight Key Threats to Internal Validity \\ Basic Issues in Designing an Experiment \\ Validity in Experiments \\ The Big Picture: Benefits and Limits of Experimental Design \\ Chapter Resources \\ Chapter 11 • Independent-Groups Designs \\ Learning Objectives \\ Designs with Independent Groups \\ Designing a Simple Experiment \\ Analysis of Two Independent-Groups Designs \\ FORMULAS and CALCULATIONS: Independent-Samples t Test \\ Using a Data Analysis Program to Calculate Independent Samples t Tests \\ Designs with More than Two Independent Groups \\ Analysis of Multiple Independent-Groups Designs \\ Formulas and Calculations: One-Way Independent-Samples ANOVA \\ Using a Data Analysis Program to Calculate One-Way Independent-Samples ANOVAs \\ The Big Picture: Identifying and Analyzing Independent-Groups Designs \\ Chapter Resources \\ Chapter 12 • Dependent-Groups Designs \\ Learning Objectives \\ Designs with Dependent Groups \\ Designs with More than two Dependent Groups \\ Analysis of Dependent Multiple-Groups Designs \\ Formulas and Calculations: Within-Subjects ANOVA \\ The Big Picture: Selecting Analyses and Interpreting Results for Dependent-Groups Designs \\ Chapter Resources \\ Chapter 13 • Factorial Designs \\ Learning Objectives \\ Basic Concepts in Factorial Design \\ Rationale for Factorial Designs \\ 2 × 2 DESIGNS \\ Two-Way Between Subjects ANOVA \\ Beyond the 2 × 2 Independent-Groups Design \\ The Big Picture: Embracing Complexity \\ Chapter Resources \\ Chapter 14 • Nonparametric Statistics \\ Learning Objectives \\ Parametric Versus Nonparametric Statistics \\ Chi-Square Goodness of Fit \\ Chi-Square Test For Independence \\ Dependent-Groups Designs with Nominal Outcome Measures \\ Spearman’s Rho to Examine Relationships Between Ordinal (Ranked) Data \\ Nonparametric Statistics for Independent- and Dependent-Groups Designs with Ordinal Data \\ The Big Picture: Selecting Parametric Versus Nonparametric Tests \\ Chapter Resources \\ Chapter 15 • Focusing on the Individual: Case Studies and Single N Designs \\ Learning Objectives \\ Samples Versus Individuals \\ The Case Study \\ Qualitative Analyses \\ Single N Designs \\ The Big Picture: Choosing Between a Sample, Case Study, or Single N Design \\ Chapter Resources \\ Chapter 16 • How to Decide? Choosing a Research Design and Selecting the Correct Analysis \\ Learning Objectives \\ Choosing a Research Design \\ Selecting Your Statistical Analyses \\ The Big Picture: Beyond This Class \\ Chapter Resources \\ Appendix A • Answers to Practice Questions \\ Appendix B • APA Style and Format Guidelines \\ Appendix C • Statistical Tables \\ Appendix D • Statistical Formulas \\ Glossary \\ References \\ Index
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