July, 2019 | SAGE Publications, Inc
Lab Manual for Psychological Research and Statistical Analysis
First Edition Dawn M. McBride - Illinois State University, USA John C. Cutting - Illinois State University, USA
160 pages | July, 2019 | SAGE Publications, Inc
Courses
| Statistics in Psychology
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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.
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Introduction for Instructors
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
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
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
4a: Distributions and Probability
4b: Basic Probability
4c: Subject Sampling
4d: Sampling
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
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
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
8a: Bias and Control Exercise
8b: Experimental Variables
8c: Experiments Exercise
8d: Experimental Designs
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
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
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
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
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
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
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
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
- 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.
