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| Preface | |
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| To the Student | |
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| Statistical Preliminaries | |
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| Introduction and Mathematical Preliminaries | |
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| The Study of Statistics | |
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| Research in the Behavioral Sciences | |
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| Variables | |
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| Measurement | |
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| Discrete and Continuous Variables | |
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| Populations and Samples | |
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| Biased Sampling | |
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| Descriptive and Inferential Statistics | |
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| The Concept of Probability | |
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| Mathematical Preliminaries: A Review | |
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| Statistics and Computers | |
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| Summary | |
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| Frequency and Probability Distributions | |
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| Frequency Distributions for Quantitative Variables: Ungrouped Scores | |
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| Frequency Distributions for Quantitative Variables: Grouped Scores | |
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| Frequency Distributions for Qualitative Variables | |
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| Outliers | |
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| Frequency Graphs | |
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| Misleading Graphs | |
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| Graphs of Relative Frequencies, Percentages, Cumulative Frequencies, and Cumulative Relative Frequencies | |
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| Probability Distributions | |
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| Empirical and Theoretical Distributions | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Measures of Central Tendency and Variability | |
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| Measures of Central Tendency for Quantitative Variables | |
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| Measures of Variability for Quantitative Variables | |
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| Computational Formula for the Sum of Squares | |
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| Relationship Between Central Tendency and Variability | |
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| Graphs of Central Tendency and Variability | |
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| Measures of Central Tendency and Variability for Qualitative Variables | |
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| Skewness and Kurtosis | |
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| Sample Versus Population Notation | |
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| Method of Presentation | |
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| Example from the Literature | |
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| Summary | |
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| Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution | |
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| Percentiles and Percentile Ranks | |
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| Standard Scores | |
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| Standard Scores and the Normal Distribution | |
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| Standard Scores and the Shape of the Distribution | |
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| Method of Presentation | |
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| Summary | |
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| The Normal Distribution Formula | |
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| Pearson Correlation and Regression: Descriptive Aspects | |
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| Use of Pearson Correlation | |
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| The Linear Model | |
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| The Pearson Correlation Coefficient | |
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| Correlation and Causation | |
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| Interpreting the Magnitude of a Correlation Coefficient | |
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| Regression | |
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| Additional Issues Associated with the Use of Correlation and Regression | |
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| Summary | |
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| Probability | |
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| Probabilities of Simple Events | |
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| Conditional Probabilities | |
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| Joint Probabilities | |
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| Adding Probabilities | |
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| Relationships Among Probabilities | |
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| Sampling with Versus Without Replacement | |
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| Beliefs and Probability Theory | |
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| Counting Rules | |
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| The Binomial Expression | |
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| Summary | |
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| Estimation and Sampling Distributions | |
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| Finite Versus Infinite Populations | |
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| Estimation of the Population Mean | |
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| Estimation of the Population Variance and Standard Deviation | |
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| Degrees of Freedom | |
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| Sampling Distribution of the Mean and the Central Limit Theorem | |
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| Polls and Random Samples | |
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| Types of Sampling Distributions | |
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| Summary | |
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| Hypothesis Testing: Inferences About a Single Mean | |
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| A Simple Analogy for Principles of Hypothesis Testing | |
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| Statistical Inference and the Normal Distribution: The One-Sample z Test | |
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| Defining Expected and Unexpected Results | |
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| Failing to Reject Versus Accepting the Null Hypothesis | |
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| Type I and Type II Errors | |
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| Effects of Alpha and Sample Size on the Power of Statistical Tests | |
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| Statistical and Real-World Significance | |
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| Directional Versus Nondirectional Tests | |
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| Statistical Inference Using Estimated Standard Errors: The One-Sample t Test | |
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| Confidence Intervals | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| The Analysis of Bivariate Relationships | |
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| Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships | |
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| Principles of Research Design: Statistical Implications | |
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| Confounding and Disturbance Variables | |
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| Selecting the Appropriate Statistical Test to Analyze a Relationship: A Preview | |
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| Summary | |
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| Independent Groups t Test | |
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| Use of the Independent Groups t Test | |
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| Inference of a Relationship Using the Independent Groups t Test | |
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| Strength of the Relationship | |
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| Nature of the Relationship | |
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| Methodological Considerations | |
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| Numerical Example | |
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| Planning an Investigation Using the Independent Groups t Test | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Correlated Groups t Test | |
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| Use of the Correlated Groups t Test | |
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| Inference of a Relationship Using the Correlated Groups t Test | |
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| Strength of the Relationship | |
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| Nature of the Relationship | |
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| Methodological Considerations | |
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| Power of Correlated Groups Versus Independent Groups t Tests | |
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| Numerical Example | |
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| Planning an Investigation Using the Correlated Groups t Test | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Computational Procedures for the Nullified Score Approach | |
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| One-Way Between-Subjects Analysis of Variance | |
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| Use of One-Way Between-Subjects Analysis of Variance | |
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| Inference of a Relationship Using One-Way Between-Subjects Analysis of Variance | |
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| Relationship of the F Test to the t Test | |
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| Strength of the Relationship | |
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| Nature of the Relationship | |
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| Unstandardized Effect Sizes and Confidence Intervals | |
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| Methodological Considerations | |
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| Numerical Example | |
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| Planning an Investigation Using One-Way Between-Subjects Analysis of Variance | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Rationale for the Degrees of Freedom | |
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| One-Way Repeated Measures Analysis of Variance | |
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| Use of One-Way Repeated Measures Analysis of Variance | |
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| Inference of a Relationship Using One-Way Repeated Measures Analysis of Variance | |
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| Strength of the Relationship | |
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| Nature of the Relationship | |
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| Unstandardized Effect Size and Confidence Intervals | |
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| Methodological Considerations | |
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| Numerical Example | |
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| Planning an Investigation Using One-Way Repeated Measures Analysis of Variance | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Determining the Nature of the Relationship Under Sphericity Violations | |
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| Pearson Correlation and Regression: Inferential Aspects | |
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| Use of Pearson Correlation | |
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| Inference of a Relationship Using Pearson Correlation | |
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| Strength of the Relationship | |
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| Confidence Intervals for the Correlation Coefficient | |
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| Nature of the Relationship | |
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| Planning an Investigation Using Pearson Correlation | |
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| Method of Presentation for Pearson Correlation | |
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| Examples from the Literature | |
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| Regression | |
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| Numerical Example | |
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| Method of Presentation for Regression | |
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| Summary | |
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| Testing Null Hypotheses Other Than [rho] = 0 | |
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| Confidence Intervals for the Correlation Coefficient | |
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| Chi-Square Test | |
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| Use of the Chi-Square Test | |
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| Two-Way Contingency Tables | |
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| Chi-Square Tests of Independence and Homogeneity | |
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| Inference of a Relationship Using the Chi-Square Test | |
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| 2 x 2 Tables | |
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| Strength of the Relationship | |
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| Nature of the Relationship | |
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| Methodological Considerations | |
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| Numerical Example | |
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| Use of Quantitative Variables in the Chi-Square Test | |
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| Planning an Investigation Using the Chi-Square Test | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Chi-Square Goodness-of-Fit Test | |
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| Summary | |
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| Determining the Nature of the Relationship Using a Modified Bonferroni Procedure | |
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| Nonparametric Statistics | |
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| Rank Scores | |
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| Nonparametric Statistics and Outliers | |
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| Analysis of Ranked Data Using Parametric Formulas | |
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| Rank Tests for Two Independent Groups | |
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| Rank Test for Two Correlated Groups | |
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| Rank Test for Three or More Independent Groups | |
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| Rank Test for Three or More Correlated Groups | |
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| Rank Test for Correlation | |
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| Examples from the Literature | |
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| Summary | |
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| Corrections for Ties for Nonparametric Rank Tests | |
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| Additional Topics | |
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| Two-Way Between-Subjects Analysis of Variance | |
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| Factorial Designs | |
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| Use of Two-Way Between-Subjects Analysis of Variance | |
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| The Concepts of Main Effects and Interactions | |
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| Inference of Relationships Using Two-Way Between-Subjects Analysis of Variance | |
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| Strength of the Relationships | |
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| Nature of the Relationships | |
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| Methodological Considerations | |
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| Numerical Example | |
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| Unequal Sample Sizes | |
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| Planning an Investigation Using Two-Way Between-Subjects Analysis of Variance | |
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| Method of Presentation | |
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| Examples from the Literature | |
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| Summary | |
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| Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs | |
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| Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships | |
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| Case I: The Relationship Between Two Qualitative Variables | |
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| Case II: The Relationship Between a Qualitative Independent Variable and a Quantitative Dependent Variable | |
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| Case III: The Relationship Between a Quantitative Independent Variable and a Qualitative Dependent Variable | |
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| Case IV: The Relationship Between Two Quantitative Variables | |
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| Procedures for More Complex Designs | |
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| Alternative Approaches to Null Hypothesis Testing | |
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| Summary | |
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| Table of Random Numbers | |
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| Proportions of Scores in a Normal Distribution | |
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| Factorials | |
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| Critical Values for the t Distribution | |
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| Power and Sample Size | |
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| Critical Values for the F Distribution | |
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| Studentized Range Values (q) | |
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| Critical Values for Pearson r | |
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| Fisher's Transformation of Pearson r(r') | |
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| Critical Values for the Chi-Square Distribution | |
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| Critical Values for the Mann-Whitney U Test | |
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| Critical Values for the Wilcoxon Signed-Rank Test | |
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| Critical Values for Spearman r | |
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| Formulas for Unbiased Estimators of Proportion of Explained Variance | |
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| Answers to Selected Exercises | |
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| Glossary of Major Symbols | |
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| References | |
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| Index | |
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| Credits | |