Research methods, statistics, and applications. ([2019])

• Record Type: Book
• Further Information: Note: Kathrynn A. Adams, Guilford College, Eva K. Lawrence, Guilford College.
• Authors: Adams, Kathrynn Ann; Lawrence, Eva K
• Contents: 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; Reliability and Validity Broadly Defined; Reliability and Validity of Measurement; Constructs and Operational Definitions; Types of Measures; Assessing Reliability of Measures; Using Data Analysis Programs: Measurement Reliability; 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 Significane; 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; 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 Vs. Correlational; 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; Limits to Experimental Design; Chapter 10. Independent-Groups Design; Designs with Independent Groups; Designing a Simple Experiment; Independent Samples t-Tests; Confidence Intervals; Using SPSS to Analyze Data From a Two Independent-Groups Design; Designs With More Than Two Independent Groups; Overview; Chapter 11. Dependent-Groups Designs; Dependent-Groups Designs; Formulas and Calculations: Dependent-Samples t-Test; Designs with More than Two Dependent Groups; Formulas and Calculations: Within-Subjects ANOVA; Using Data Analysis Programs: Within-Subjects ANOVA; 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 Non-parametric Statistics; Non-parametric Tests for Nominal Data; Formulas and Calculations: Chi-Square Goodness of Fit; Using Data Analysis Programs: Chi-Square Test for Independence; Non-parametric Statistics for Ordinal (Ranked) Data; Formulas and Calculations: Spearman's Rho; Using Data Analysis Programs: Spearman's Rho; The Big Picture: Selecting Parametric Vs. Non-parametric Tests; Chapter 14. Focusing on the Individual; 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?; 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;
• Edition: Second edition
• Publisher Details: Los Angeles : SAGE Publications
• Publication Date: 2019
• Extent: 1 online resource (xxv, 646 pages), illustrations
• Subjects: 001.422; Research -- Statistical methods; Research -- Methodology; Statistics
• Languages: English
• ISBNs: 9781506350448; 1506350445
• Related ISBNs: 9781506350455
• Notes: Note: Includes bibliographical references and index.
• Access Rights: 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).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.