Statistics for Psychology Plus NEW MyStatLab with eText / Edition 6

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Overview

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Emphasizing meaning and concepts, not just symbols and numbers

Statistics for Psychology, 6th edition places definitional formulas center stage to emphasize the logic behind statistics and discourage rote memorization. Each procedure is explained in a direct, concise language and both verbally and numerically.

MyStatLab is an integral part of the Statistics course. MyStatLab gives students practice with hundreds of homework problems. Every problem includes tools to help students understand and solve each problem - and grades all of the problems for instructors. MyStatLab also includes tests, quizzes, eText, a Gradebook, a customizable study plan, and much more.

Learning Goals

Upon completing this book, readers should be able to:

  • Know both definitional and numerical formulas and how to apply them
  • Understand the logic behind each formula
  • Expose students to the latest thinking in statistical theory and application
  • Prepare students to read research articles
  • Learn how to use SPSS
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Editorial Reviews

From the Publisher

“I like the order in which the topics are presented. The order is the same way that I would choose if I were writing a text myself.”

- Kathleen Denson, Texas A&M Commerce

“Aron et al. strives to make statistical concepts accessible to students who may not have a background or interests in math.”

- Brock Kirwan, Brigham Young University

“This text is at a level that I would feel comfortable assigning to my intro stats students.”

- Osvaldo Morera, University of Texas at El Paso

“I like that [the text] introduced students to more complex techniques in an effort to help them to understand the articles that they are reading with more complex statistics in them”

-Stacey Williams, East Tennessee State University

“.The Level of writing is it’s strongest assets. Very clear step by step instructions. The level of writing is very appropriate to my students”

-Stephen Armeli, Farleigh Dickinson

“High-level, clear, comprehensive. The book is effective at helping students understand the material”

- Kristin Lane, Bard College

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Product Details

  • ISBN-13: 9780205924172
  • Publisher: Pearson
  • Publication date: 9/10/2012
  • Edition description: New Edition
  • Edition number: 6
  • Pages: 744
  • Sales rank: 215,220
  • Product dimensions: 8.20 (w) x 10.20 (h) x 1.20 (d)

Table of Contents

In this Section:

1. Brief Table of Contents

2. Full Table of Contents


1. BRIEF TABLE OF CONTENTS

Chapter 1 Displaying the order in a group of numbers

Chapter 2 Central tendency and variability

Chapter 3 Some key ingredients for inferential statistics: Z scores, the normal curve, sample versus

population, and probability

Chapter 4 Introduction to hypothesis testing

Chapter 5 Hypothesis testing with means of samples

Chapter 6 Making sense of statistical significance: Effect size and statistical power

Chapter 7 Introduction to the t test: Single sample and dependent means

Chapter 8 The t test for independent means

Chapter 9 Introduction to the analysis of variance

Chapter 10 Factorial analysis of variance

Chapter 11 Correlation

Chapter 12 Prediction

Chapter 13 Chi-square tests

Chapter 14 Strategies when population distributions are not normal: Data transformations and rank-order

tests

Chapter 15 Integration and the general linear model and Making sense of advanced statistical procedures in

research articles


2. FULL TABLE OF CONTENTS

Chapter 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

Chapter 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

Chapter 3: Some key ingredients for inferential statistics: Z scores, 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

Chapter 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

Chapter 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

Chapter 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

Chapter 7: Introduction to the t test: Single sample and dependent means

The t Test for a Single Sample

The t Test for Dependent Means

Assumptions of the t Test for a Single Sample and the t Test for Dependent Means

Controversy: Advantages and Disadvantages of Repeated-Measures Designs

Single Sample t Tests and Dependent Means t Tests in Research Articles

Summary

Key Terms

Example Worked-Out Problems

Practice Problems

Using SPSS

Chapter Note

Chapter 8: The t test for independent means

The Distribution of Differences Between Means

Hypothesis Testing with a t Test for Independent Means

Assumptions of the t Test for Independent Means

Effect Size and Power for the t Test for Independent Means

Review and Comparison of the Three Kinds of t Tests

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

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 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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