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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.

For instructors

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