Research methods, statistics, and applications. (2018)
- Record Type:
- Book
- Title:
- Research methods, statistics, and applications. (2018)
- Main Title:
- Research methods, statistics, and applications
- Further Information:
- Note: Kathrynn A. Adams, Eva K. Lawrence.
- Authors:
- Adams, Kathrynn Ann
Lawrence, Eva K - Contents:
- 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 AnalysisPreface; 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<br /> 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; … (more)
- Edition:
- Second edition
- Publisher Details:
- Los Angeles : SAGE
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 001.422
Research -- Statistical methods - Languages:
- English
- ISBNs:
- 9781506350479
- Notes:
- Note: Includes bibliographical references and index.
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- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- British Library HMNTS - ELD.DS.269333
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