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| Concepts and Examples of Research | |
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| Concepts | |
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| Examples | |
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| Concluding Remarks | |
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| References | |
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| Classification of Variables and the Choice of Analysis | |
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| Classification of Variables | |
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| Overlapping of Classification Schemes | |
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| Choice of Analysis | |
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| References | |
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| Basic Statistics: A Review | |
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| Preview | |
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| Descriptive Statistics | |
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| Random Variables and Distributions | |
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| Sampling Distributions of t, ?+2, and F | |
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| Statistical Inference: Estimation | |
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| Statistical Inference: Hypothesis Testing | |
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| Error Rate, Power, and Sample Size | |
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| Problems | |
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| References | |
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| Introduction to Regression Analysis | |
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| Preview | |
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| Association versus Causality | |
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| Statistical versus Deterministic Models | |
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| Concluding Remarks | |
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| References | |
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| Straight-Line Regression Analysis | |
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| Preview | |
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| Regression with a Single Independent Variable | |
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| Mathematical Properties of a Straight Line | |
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| Statistical Assumptions for a Straight-line Model | |
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| Determining the Best-fitting Straight Line | |
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| Measure of the Quality of the Straight-line Fit and Estimate? | |
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| Inferences About the Slope and Intercept | |
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| Interpretations of Tests for Slope and Intercept | |
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| Inferences About the Regression Line ?&YX = ?-0 + ?-1X | |
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| Prediction of a New Value of Y at X | |
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| Problems | |
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| References | |
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| The Correlation Coefficient and Straight-Line Regression Analysis | |
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| Definition of r | |
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| r as a Measure of Association | |
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| The Bivariate Normal Distribution | |
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| r and the Strength of the Straight-line Relationship | |
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| What r Does Not Measure | |
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| Tests of Hypotheses and Confidence Intervals for the Correlation Coefficient | |
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| Testing for the Equality of Two Correlations | |
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| Problems | |
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| References | |
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| The Analysis-of-Variance Table | |
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| Preview | |
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| The ANOVA Table for Straight-line Regression | |
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| Problems | |
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| Multiple Regression Analysis: General Considerations | |
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| Preview | |
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| Multiple Regression Models | |
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| Graphical Look at the Problem | |
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| Assumptions of Multiple Regression | |
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| Determining the Best Estimate of the Multiple Regression Equation | |
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| The ANOVA Table for Multiple Regression | |
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| Numerical Examples | |
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| Problems | |
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| References | |
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| Testing Hypotheses in Multiple Regression | |
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| Preview | |
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| Test for Significant Overall Regression | |
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| Partial F Test | |
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| Multiple Partial F Test | |
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| Strategies for Using Partial F Tests | |
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| Tests Involving the Intercept | |
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| Problems | |
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| References | |
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| Correlations: Multiple, Partial, and Multiple Partial | |
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| Preview | |
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| Correlation Matrix | |
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| Multiple Correlation Coefficient | |
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| Relationship of RYX1, X2, mKXk to the Multivariate Normal Distribution | |
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| Partial Correlation Coefficient | |
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| Alternative Representation of the Regression Model | |
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| Multiple Partial Correlation | |
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| Concluding Remarks | |
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| Problems | |
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| References | |
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| Confounding and Interaction in Regression | |
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| Preview | |
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| Overview | |
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| Interaction in Regression | |
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| Confounding in Regression | |
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| Summary and Conclusions | |
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| Problems | |
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| References | |
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| Dummy Variables in Regression | |
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| Preview | |
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| Definitions | |
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| Rule for Defining Dummy Variables | |
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| Comparing Two Straight-line Regression Equations: An Example | |
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| Questions for Comparing Two Straight Lines | |
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| Methods of Comparing Two Straight Lines | |
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| Method I: Using Separate Regression Fits to Compare Two Straight Lines | |
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| Method II: Using a Single Regression Equation to Compare Two Straight Lines | |
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| Comparison of Methods I and II | |
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| Testing Strategies and Interpretation: Comparing Two Straight Lines | |
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| Other Dummy Variable Models | |
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| Comparing Four Regression Equations | |
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| Comparing Several Regression Equations Involving Two Nominal Variables | |
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| Problems | |
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| References | |
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| Analysis of Covariance and Other Methods for Adjusting Continuous Data | |
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| Preview | |
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| Adjustment Problem | |
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| Analysis of Covariance | |
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| Assumption of Parallelism: A Potential Drawback | |
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| Analysis of Covariance: Several Groups and Several Covariates | |
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| Comments and Cautions | |
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| Summary Problems | |
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| Reference | |
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| Regression Diagnostics | |
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| Preview | |
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| Simple Approaches to Diagnosing Problems in Data | |
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| Residual Analysis: Detecting Outliers and Violations of Model Assumptions | |
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| Strategies of Analysis | |
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| Collinearity | |
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| Scaling Problems | |
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| Diagnostics Example | |
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| An Important Caution | |
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| Problems | |
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| References | |
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| Polynomial Regression | |
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| Preview | |
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| Polynomial | |