Description
Solution Manual for Research Methods, Statistics, and Applications 2nd Edition Adams
Solution Manual for Research Methods, Statistics, and Applications, 2nd Edition, Kathrynn A. Adams, Eva K. Lawrence, ISBN: 9781506350455, ISBN: 9781544330167, ISBN: 9781544332659
Table Of Content
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
