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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 | |