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Lab Manual for Psychological Research and Statistical Analysis

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
Key features
  • Activities that guide students through research and literature reviews and writing in APA Style
  • Projects with data sets allow students to practice analysis and carry out a capstone project.
  • Meet the Formulae features help students see conceptual similarities across formulae.
  • Workbook/Homework exercises for each major topic in the course provide extra practice for students and homework problems for instructors to assign.
  • Connections between research designs and statistical tests help students figure out which test to use when given a research study or data set.

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