What is included with this book?
Concepts and Examples of Research | |
Concepts | |
Examples | |
Concluding Remarks | |
References | |
Classification of Variables and the Choice of Analysis | |
Classification of Variables | |
Overlapping of Classification Schemes | |
Choice of Analysis | |
References | |
Basic Statistics: A Review | |
Preview | |
Descriptive Statistics | |
Random Variables and Distributions | |
Sampling Distributions of t, ?+2, and F | |
Statistical Inference: Estimation | |
Statistical Inference: Hypothesis Testing | |
Error Rate, Power, and Sample Size | |
Problems | |
References | |
Introduction to Regression Analysis | |
Preview | |
Association versus Causality | |
Statistical versus Deterministic Models | |
Concluding Remarks | |
References | |
Straight-Line Regression Analysis | |
Preview | |
Regression with a Single Independent Variable | |
Mathematical Properties of a Straight Line | |
Statistical Assumptions for a Straight-line Model | |
Determining the Best-fitting Straight Line | |
Measure of the Quality of the Straight-line Fit and Estimate? | |
Inferences About the Slope and Intercept | |
Interpretations of Tests for Slope and Intercept | |
Inferences About the Regression Line ?&Y X = ?-0 + ?-1X | |
Prediction of a New Value of Y at X | |
Problems | |
References | |
The Correlation Coefficient and Straight-Line Regression Analysis | |
Definition of r | |
r as a Measure of Association | |
The Bivariate Normal Distribution | |
r and the Strength of the Straight-line Relationship | |
What r Does Not Measure | |
Tests of Hypotheses and Confidence Intervals for the Correlation Coefficient | |
Testing for the Equality of Two Correlations | |
Problems | |
References | |
The Analysis-of-Variance Table | |
Preview | |
The ANOVA Table for Straight-line Regression | |
Problems | |
Multiple Regression Analysis: General Considerations | |
Preview | |
Multiple Regression Models | |
Graphical Look at the Problem | |
Assumptions of Multiple Regression | |
Determining the Best Estimate of the Multiple Regression Equation | |
The ANOVA Table for Multiple Regression | |
Numerical Examples | |
Problems | |
References | |
Testing Hypotheses in Multiple Regression | |
Preview | |
Test for Significant Overall Regression | |
Partial F Test | |
Multiple Partial F Test | |
Strategies for Using Partial F Tests | |
Tests Involving the Intercept | |
Problems | |
References | |
Correlations: Multiple, Partial, and Multiple Partial | |
Preview | |
Correlation Matrix | |
Multiple Correlation Coefficient | |
Relationship of RY X1, X2, mKXk to the Multivariate Normal Distribution | |
Partial Correlation Coefficient | |
Alternative Representation of the Regression Model | |
Multiple Partial Correlation | |
Concluding Remarks | |
Problems | |
References | |
Confounding and Interaction in Regression | |
Preview | |
Overview | |
Interaction in Regression | |
Confounding in Regression | |
Summary and Conclusions | |
Problems | |
References | |
Dummy Variables in Regression | |
Preview | |
Definitions | |
Rule for Defining Dummy Variables | |
Comparing Two Straight-line Regression Equations: An Example | |
Questions for Comparing Two Straight Lines | |
Methods of Comparing Two Straight Lines | |
Method I: Using Separate Regression Fits to Compare Two Straight Lines | |
Method II: Using a Single Regression Equation to Compare Two Straight Lines | |
Comparison of Methods I and II | |
Testing Strategies and Interpretation: Comparing Two Straight Lines | |
Other Dummy Variable Models | |
Comparing Four Regression Equations | |
Comparing Several Regression Equations Involving Two Nominal Variables | |
Problems | |
References | |
Analysis of Covariance and Other Methods for Adjusting Continuous Data | |
Preview | |
Adjustment Problem | |
Analysis of Covariance | |
Assumption of Parallelism: A Potential Drawback | |
Analysis of Covariance: Several Groups and Several Covariates | |
Comments and Cautions | |
Summary Problems | |
Reference | |
Regression Diagnostics | |
Preview | |
Simple Approaches to Diagnosing Problems in Data | |
Residual Analysis: Detecting Outliers and Violations of Model Assumptions | |
Strategies of Analysis | |
Collinearity | |
Scaling Problems | |
Diagnostics Example | |
An Important Caution | |
Problems | |
References | |
Polynomial Regression | |
Preview | |
Polynomial | |
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