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Lab Manual for Psychological Research and Statistical Analysis
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Lab Manual for Psychological Research and Statistical Analysis

First Edition


August 2019 | 160 pages | SAGE Publications, Inc
Lab Manual for Psychological Research and Statistical Analysis 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. Packed with exercises, checklists, and how-to sections, this robust lab manual gives students hands-on guidance and practice for conducting and analyzing their own psychological research. Dawn M. McBride and J. Cooper Cutting provide students with additional opportunities for practice in a course with challenging material that requires practice and repetition for deeper understanding.
 
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

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Dawn M. McBride

Dawn M. McBride is a professor of psychology at Illinois State University. Her research interests include automatic forms of memory, false memory, prospective memory, and forgetting. She has taught courses in introductory psychology, statistics, research methods, cognition and learning, human memory, and a graduate course in experimental design. She is a recipient of the Illinois State University Teaching Initiative Award. Her out-of-work interests include spending time with her family, traveling, watching Philadelphia (her place of birth) sports teams, learning new languages (currently, Japanese) and reading British murder mysteries. She... More About Author

John C. Cutting

J. Cooper Cutting (PhD, cognitive psychology, University of Illinois, Urbana-Champaign) is associate professor of psychology at Illinois State University. Dr. Cutting’s research interests are in psycholinguistics, primarily with a focus on the production of language. A central theme of his research is how different types of information interact during language use. He has examined this issue in the context of lexical access, within-sentence agreement processes, figurative language production, and pragmatics. He teaches courses in research methods, statistics, cognitive psychology, computer applications in psychology, human memory,... More About Author

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ISBN: 9781544363493
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