## 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