Statistics for Psychology

Statistics for Psychology, 6th edition

  • Arthur Aron, 
  • Elliot J. Coups, 
  • Elaine N. Aron

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Overview

Statistics for Psychology emphasizes meaning and concepts -- not just symbols and numbers -- and discourages rote memorization. Each procedure is explained in a direct, concise language and both verbally and numerically.

Published by Pearson (July 23rd 2021) - Copyright © 2013

ISBN-13: 9780137477968

Subject: Statistics, Introductory

Category: Statistics for Social Sciences

Table of contents

In this Section:
1. Brief Table of Contents
2. Full Table of Contents

BRIEF TABLE OF CONTENTS
1. Displaying the order in a group of numbers
2. Central tendency and variability
3. Some key ingredients for inferential statistics:Zscores, the normal curve, sample versus population, and probability
4. Introduction to hypothesis testing
5. Hypothesis testing with means of samples
6. Making sense of statistical significance: Effect size and statistical power
7. Introduction to thettest: Single sample and dependent means
8. Thettest for independent means
9. Introduction to the analysis of variance
10. Factorial analysis of variance
11. Correlation
12. Prediction
13. Chi-square tests
14. Strategies when population distributions are not normal: Data transformations and rank-order tests
15. Integration and the general linear model and Making sense of advanced statistical procedures in research articles

FULL TABLE OF CONTENTS
1. Displaying the order in a group of numbers
The Two Branches of Statistical Methods
Some Basic Concepts
Frequency Tables
Histograms
Shapes of Frequency Distributions
Controversy: Misleading Graphs
Frequency Tables and Histograms in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

2. Central tendency and variability
Central Tendency
Variability
Controversy: The Tyranny of the Mean
Central Tendency and Variability in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

3. Some key ingredients for inferential statistics:Zscores, the normal curve, sample versus population, and probability
Z Scores
The Normal Curve
Sample and Population
Probability
Controversies: Is the Normal Curve Really So Normal? And Using Nonrandom Samples
Z Scores, Normal Curves, Samples and Populations, and Probabilities in Research Articles
Advanced Topics: Probability Rules and Conditional Probabilities
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

4. Introduction to hypothesis testing
A Hypothesis-Testing Example
The Core Logic of Hypothesis Testing
The Hypothesis-Testing Process
One-Tailed and Two-Tailed Hypothesis Tests
Controversy: Should Significance Tests Be Banned?
Hypothesis Tests in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

5. Hypothesis testing with means of samples
The Distribution of Means
Hypothesis Testing with a Distribution of Means: The Z Test
Controversy: Marginal Significance
Hypothesis Tests About Means of Samples (Z Tests) and Standards Errors in Research Articles
Advanced Topic: Estimation, Standard Errors, and Confidence Intervals
Advanced Topic Controversy: Confidence Intervals versus Significance Tests
Advance Topic: Confidence Intervals in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

6. Making sense of statistical significance: Effect size and statistical power
Decision Errors
Effect Size
Statistical Power
What Determines the Power of Study
The Role of Power Interpreting the Results of a Study
Controversy: Statistical Significance versus Effect Size
Decision Errors, Effect Size, and Power in Research Articles
Advanced Topics; Figuring Statistical Power
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

7. Introduction to thettest: Single sample and dependent means
ThetTest for a Single Sample
ThetTest for Dependent Means
Assumptions of thetTest for a Single Sample and thetTest for Dependent Means
Controversy: Advantages and Disadvantages of Repeated-Measures Designs
Single SampletTests and Dependent MeanstTests in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

8. Thettest for independent means
The Distribution of Differences Between Means
Hypothesis Testing with atTest for Independent Means
Assumptions of thetTest for Independent Means
Effect Size and Power for thetTest for Independent Means
Review and Comparison of the Three Kinds oftTests
The t Test for Independent Means in Research Articles
Advanced Topic: Power for the t Test for Independent Means When Sample Sizes Are Not Equal
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

9. Introduction to the analysis of variance
Basic Logic of the Analysis of Variance
Carrying Out an Analysis of Variance
Hypothesis Testing with the Analysis of Variance
Assumptions in the Analysis of Variance
Planned Contrasts
Post Hoc Comparisons
Effect Size and Power for the Analysis of Variance
Controversy: Omnibus Tests versus Planned Contrasts
Analyses of Variance in Research Articles
Advanced Topic: The Structural Model in the Analysis of Variance
Principles of the Structural Model
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

10. Factorial analysis of variance
Basic Logic of Factorial Designs and Interaction Effects
Recognizing and Interpreting Interaction Effect
Basic Logic of the Two-Way Analysis of Variance
Assumptions in the Factorial Analysis of Variance
Extensions and Special Cases of the Analysis of Variance
Controversy: Dichotomizing Numeric Variables
Factorial Analysis of Variance in Research Articles
Advanced Topic: Figuring a Two-Way Analysis of Variance
Advanced Topic: Power and Effect Size in the Factorial Analysis of Variance
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

11. Correlation
Graphing Correlations: The Scatter Diagram
Patterns in Correlation
The Correlation Coefficient
Significance of a Correlation Coefficient
Correlation and Causality
Issues in Interpreting the Correlation Coefficient
Effect Size and Power for the Correlation Coefficient
Controversy: What is a Large Correlation?
Correlation in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

12. Prediction
Predictor (X) and Criterion (Y) Variables
The Linear Prediction Rule
The Regression Line
Finding the Best Linear Prediction Rule
The Least Squared Error Principle
Issues in Prediction
Multiple Regression
Limitations of Prediction
Controversy: Unstandardized and Standardized Regression Coefficients; Comparing Predictors
Prediction in Research Articles
Advanced Topic: Error and Proportionate Reduction in Error
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

13. Chi-square tests
The Chi-Square Statistic and the Chi-Square Test for Goodness of Fit
The Chi-Square Test for Independence
Assumptions for Chi-Square Tests
Effect Size and Power for Chi-Tests for Independence
Controversy: The Minimum Expected Frequency
Chi-Square Tests in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

14. Strategies when population distributions are not normal: Data transformations and rank-order tests
Assumptions in the Standard Hypothesis-Testing Procedures
Data Transformations
Rank-Order Tests
Comparison of Methods
Controversy: Computer-Intensive Methods
Data Transformations and Rank-Order Tests in Research Articles
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

15. Integration and the general linear model and Making sense of advanced statistical procedures in research articles
The General Linear
Partial Correlation
Reliability
Multilevel Modeling
Factor Analysis
Casual Modeling
Procedures That Compare Groups
Analysis of Covariance (ANCOVA)
Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of Covariance (MANCOVA)
Overview of Statistical Techniques
Controversy: Should Statistics Be Controversial?
How to Read Results Using Unfamiliar Statistical Techniques
Summary
Key Terms
Example Worked-Out Problems
Practice Problems
Using SPSS
Chapter Note

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