Dawn M. McBride, J. Cooper Cutting

Lab Manual for Psychological Research and Statistical Analysis

• Broschiertes Buch

Produktbeschreibung

This lab manual serves as an additional resource for students and instructors in a research methods, statistics, or combined course where classroom and/or laboratory exercises are conducted.

Produktdetails

• Verlag: SAGE Publications Inc
• Seitenzahl: 160
• Erscheinungstermin: 14. November 2019
• Englisch
• Abmessung: 217mm x 283mm x 15mm
• Gewicht: 404g
• ISBN-13: 9781544363493
• ISBN-10: 1544363494
• Artikelnr.: 55481405

Autorenporträt

Dawn M. McBride is professor of psychology at Illinois State University, where she has taught research methods since 1998. Her research interests include automatic forms of memory, false memory, prospective memory, task order choices, and forgetting. In addition to research methods, she teaches courses in introductory psychology, cognition and learning, and human memory; she also teaches a graduate course in experimental design. She is a recipient of the Illinois State University Teaching Initiative Award and the Illinois State University SPA/Psi Chi Jim Johnson Award for commitment to undergraduate mentorship, involvement, and achievement. Her nonacademic interests include spending time with her family, traveling, watching Philadelphia sports teams (it was a good year for Philly sports this year!), and reading British murder mysteries. She earned her PhD in cognitive psychology from the University of California, Irvine, and her BA from the University of California, Los Angeles.

Inhaltsangabe

Introduction for Instructors CHAPTER 1
Psychological Research: The Whys and Hows of the Scientific Method and Statistics 1a: The Purpose of Statistics 1b: Science in the Media 1c: Understanding Your Data 1d: Displaying Distributions 1e: Making and Interpreting Graphs 1f: Setting up Your Data in SPSS: Creating a Data File 1g: Displaying Distributions in SPSS CHAPTER 2
Developing a Research Question and Understanding Research Reports 2a: How to Read Empirical Journal Articles 2b: Reading Journal Articles-Mueller and Oppenheimer (2014) 2c: Reading Journal Articles-Roediger and Karpicke (2006) 2d: Reviewing the Literature 2e: Creating References 2f: APA Style 2g: APA-Style Manuscript Checklist CHAPTER 3
Ethical Guidelines for Psychological Research 3a: Ethics 3b: Ethics in a Published Study 3c: Academic Honesty Guidelines-What Is (and Isn't) Plagiarism 3d: Examples of Plagiarism 3e: Identifying and Avoiding Plagiarism CHAPTER 4
Probability and Sampling 4a: Distributions and Probability 4b: Basic Probability 4c: Subject Sampling 4d: Sampling CHAPTER 5
How Psychologists Use the Scientific Method: Data Collection Techniques and Research Designs 5a: Naturalistic Observation Group Activity 5b: Basics of Psychological Research 5c: Designing an Experiment Activity 5d: Research Design Exercise 5e: Design and Data Collection Exercise CHAPTER 6
Descriptive Statistics 6a: Central Tendency: Comparing Data Sets 6b: Understanding Central Tendency 6c: Central Tendency in SPSS 6d: Describing a Distribution (Calculations by Hand) 6e: More Describing Distributions 6f: Descriptive Statistics With Excel 6g: Measures of Variability in SPSS CHAPTER 7
Independent Variables and Validity in Research 7a: Identifying and Developing Hypotheses About Variables 7b: Independent and Dependent Variables 7c: Identifying Variables From Abstracts 7d: Identifying Variables From Empirical Articles 7e: Research Concepts: Designs, Validity, and Scales of Measurement 7f: Internal and External Validity CHAPTER 8
One-Factor Experiments 8a: Bias and Control Exercise 8b: Experimental Variables 8c: Experiments Exercise 8d: Experimental Designs CHAPTER 9
Hypothesis-Testing Logic 9a: Inferential Statistics Exercise 9b: Calculating z Scores Using SPSS 9c: The Normal Distribution 9d: z Scores and the Normal Distribution 9e: Hypothesis Testing With Normal Populations 9f: Hypothesis Testing With z Tests CHAPTER 10
t Tests 10a: Hypothesis Testing With a Single Sample 10b: One-Sample t Test in SPSS 10c: One-Sample t Tests by Hand 10d: Related-Samples t Tests 10e: Related-Samples t Test in SPSS 10f: Independent Samples t Tests 10g: Hypothesis Testing-Multiple Tests 10h: More Hypothesis Tests With Multiple Tests 10i: t Tests Summary Worksheet 10j: Choose the Correct t Test 10k: Writing a Results Section From SPSS Output-t Tests CHAPTER 11
One-Way Analysis of Variance 11a: One-Way Between-Subjects Analysis of Variance (Hand Calculations) 11b: One-Way Between-Subjects Analysis of Variance in SPSS 11c: Writing a Results Section From SPSS Output-Analysis of Variance 11d: Inferential Statistics and Analyses CHAPTER 12
Correlation Tests and Simple Linear Regression 12a: Creating and Interpreting Scatterplots 12b: Understanding Correlations 12c: Correlations and Scatterplots in SPSS 12d: Computing Correlations by Hand 12e: Hypothesis Testing With Correlation Using SPSS 12f: Regression CHAPTER 13
Chi-Square Tests 13a: Chi-Square Crosstabs Tables 13b: Chi-Square Hand Calculations From Crosstabs Tables 13c: Chi-Square in SPSS-Type in the Data 13d: Chi-Square in SPSS From a Data File CHAPTER 14
Multifactor Experiments and Two-Way Analysis of Variance (Chapters 14 and 15) 14a: Factorial Designs 14b: Factorial Designs Article-Sproesser, Schupp, and Renner (2014) 14c: Factorial Designs Article-Farmer, McKay, and Tsakiris (2014) 14d: Describing Main Effects and Interactions 14e: Factorial Analysis of Variance 14f: Analysis of Variance Review 14g: Main Effects and Interactions in Factorial Analysis of Variance CHAPTER 15
One-Way Within-Subjects Analysis of Variance 15a: One-Way Within-Subjects Analysis of Variance 15b: One-Way Within-Subjects Analysis of Variance in SPSS 15c: One-Way Within-Subjects Analysis of Variance Review CHAPTER 16
Meet the Formulae and Practice Computation Problems 16a: Meet the Formula and Practice Problems: z Score Transformation 16b: Meet the Formula and Practice Problems: Single-Sample z Tests and t Tests 16c: Meet the Formula and Practice Problems: Comparing Independent Samples and Related Samples t Tests 16d: Meet the Formula and Practice Problems: One-Factor Between-Subjects Analysis of Variance 16e: Meet the Formula and Practice Problems: Two-Factor Analysis of Variance 16f: Meet the Formula and Practice Problems: One-Factor Within-Subjects Analysis of Variance 16g: Meet the Formula and Practice Problems: Correlation 16h: Meet the Formula and Practice Problems: Bivariate Regression Appendix A. Data Sets and Activities A1: Data Analysis Exercise-von Hippel, Ronay, Baker, Kjelsaas, and Murphy (2016) A2: Data Analysis Exercise-Nairne, Pandeirada, and Thompson (2008) A3: Data Analysis Project-Crammed vs. Distributed Study A4: Data Analysis Project-Teaching Techniques Study A5: Data Analysis Project-Distracted Driving Study A6: Data Analysis Project-Temperature and Air Quality Study A7: Data Analysis Project-Job Type and Satisfaction Study A8: Data Analysis Project-Attractive Face Recognition Study A9: Data Analysis Project-Discrimination in the Workplace Study Appendix B. Overview and Selection of Statistical Tests B1: Finding the Appropriate Inferential Test B2: Finding the Appropriate Inferential Test From Research Designs B3: Finding the Appropriate Inferential Test From Research Questions B4: Identifying the Design and Finding the Appropriate Inferential Test From Abstracts B5: Identifying Variables and Determining the Inferential Test From Abstracts Appendix C. Summary of Formulae References