图书简介

Preface \\ About The Authors \\ Chapter 1: Thinking Like A Researcher \\ Critical Thinking \\ Thinking Critically About Ethics \\ The Scientific Approach \\ Overview of the Research Process (a.k.a. the Scientific Method) \\ The Big Picture: Proof and Progress in Science \\ Chapter 2: Build a Solid Foundation for Your Study Based On Past Research \\ Types of Sources \\ Types of Scholarly Works \\ Strategies to Identify and Find Past Research \\ Reading and Evaluating Primary Research Articles \\ Develop Study Ideas Based on Past Research \\ APA Format for References \\ The Big Picture: Use the Past to Inform the Present \\ Chapter 3: The Cornerstones of Good Research: Reliability and Validity \\ Using Data Analysis Programs: Measurement Reliability \\ Reliability and Validity Broadly Defined \\ Reliability and Validity of Measurement \\ Constructs and Operational Definitions \\ Types of Measures \\ Assessing Reliability of Measures \\ Assessing Validity of Measures \\ Reliability and Validity at the Study Level \\ The Big Picture: Consistency and Accuracy \\ Chapter 4: Basics of Research Design: Description, Measurement, and Sampling \\ When Is a Descriptive Study Appropriate? \\ Validity in Descriptive Studies \\ Measurement Methods \\ Defining the Population and Obtaining a Sample \\ The Big Picture: Beyond Description \\ Chapter 5: Describing Your Sample \\ Ethical Issues in Describing Your Sample \\ Practical Issues in Describing Your Sample \\ Descriptive Statistics \\ Choosing the Appropriate Descriptive Statistics \\ Using Data Analysis Programs: Descriptive Statistics \\ Comparing Interval/Ratio Scores with z Scores and Percentiles \\ The Big Picture: Know Your Data and Your Sample \\ Chapter 6: Beyond Descriptives: Making Inferences Based on Your Sample \\ Inferential Statistics \\ Hypothesis Testing \\ Errors in Hypothesis Testing \\ Effect Size, Confidence Intervals, and Practical Significance \\ Determining the Effect Size, Confidence Interval, and Practical Significance in a Study \\ The Big Picture: Making Sense of Results \\ Chapter 7: Comparing Your Sample to a Known or Expected Score \\ Choosing the Appropriate Test \\ One-Sample t Tests \\ Formulas and Calculations: One-Sample t Test \\ Using Data Analysis Programs: One-Sample t Test \\ Results \\ Discussion \\ The Big Picture: Examining One Variable at a Time \\ Chapter 8: Examining Relationships among Your Variables: Correlational Design \\ Correlational Design \\ Basic Statistics to Evaluate Correlational Research \\ Using Data Analysis Programs: Pearson’s r and Point-Biserial r \\ Regression \\ Formulas and Calculations: Simple Linear Regression \\ Using Data Analysis Programs: Regression \\ The Big Picture: Correlational Designs Versus Correlational Analyses \\ Chapter 9: Examining Causality \\ Testing Cause and Effect \\ Threats to Internal Validity \\ Basic Issues in Designing an Experiment \\ Other Threats to Internal Validity \\ Balancing Internal and External Validity \\ The Big Picture: Benefits and Limits of Experimental Design \\ Chapter 10: Independent-Groups Designs \\ Designs with Independent Groups \\ Designing a Simple Experiment \\ Independent-Samples t Tests \\ Formulas and calculations: independent-samples t test \\ Using data analysis programs: independent-samples t test \\ Designs With More Than Two Independent Groups \\ Formulas and calculations: one-way independent-samples anova \\ Using data analysis programs: one-way independent-samples anova \\ The big picture: identifying and analyzing independent-groups designs \\ Chapter 11: Dependent-Groups Designs \\ Designs with dependent groups \\ Formulas and Calculations: Dependent-Samples t Test \\ Using data analysis programs: dependent-samples t test \\ Designs with more than two dependent groups \\ Formulas and calculations: within-subjects ANOVA \\ Using data analysis programs: within-subjects ANOVA \\ The big picture: selecting analyses and interpreting results for dependent-groups designs \\ Chapter 12: Factorial Designs \\ Basic Concepts in Factorial Design \\ Rationale for Factorial Designs \\ 2 x 2 Designs \\ Analyzing Factorial Designs \\ Analyzing Independent-Groups Factorial Designs \\ Formulas and Calculations: Two-Way Between-Subjects ANOVA \\ Using Data Analysis Programs: Two-Way Between-Subjects ANOVA \\ Reporting and Interpreting Results of a Two-Way ANOVA \\ Dependent-Groups Factorial Designs \\ Mixed Designs \\ The Big Picture: Embracing Complexity \\ Chapter 13: Nonparametric Statistics \\ Parametric Versus Nonparametric Statistics \\ Nonparametric Tests for Nominal Data \\ Formulas and Calculations: Chi-Square Goodness of Fit \\ Using Data Analysis Programs: Chi-Square Goodness of Fit \\ Formulas and calculations: chi-square test for independence \\ Using data analysis programs: chi-square test for independence \\ Nonparametric statistics for ordinal (ranked) data \\ Formulas and calculations: spearman’s rho \\ Using data analysis programs: spearman’s rho \\ The big picture: selecting parametric versus nonparametric tests \\ Chapter 14: Focusing on the Individual Case Studies and Single N Designs \\ Samples Versus Individuals \\ The Case Study \\ Single N Designs \\ The Big Picture: Choosing Between a Sample, Case Study, or Single N Design \\ Chapter 15: How to Decide? Choosing a Research Design and Selecting the Correct Analysis \\ First and Throughout: Base Your Study on Past Research \\ Choosing a Research Design \\ Selecting Your Statistical Analyses \\ The Big Picture: Beyond This Class \\ Appendix A: Answers to Practice Questions \\ Appendix B: APA Style and Format Guidelines \\ Appendix C: Statistical Tables \\ Appendix D: Statistical Formulas \\ Glossary \\ References \\ Author index \\ Subject index

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