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Statistics for Psychology, 6th edition

Published by Pearson (July 23, 2021) © 2013

  • Arthur Aron State University of New York at Stony Brook
  • Elliot J. Coups Robert Wood Johnson Medical School, Rutgers State University of New Jersey
  • Elaine N. Aron State University of New York at Stony Brook
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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

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

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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