Applied Multiple Regression/Correlation Analysis for Aviation Research describes and illustrates multiple regression/correlation (MRC) analysis in an aviation context and is the ideal textbook for research-oriented graduate aviation programs that require knowledge of advanced statistical strategies for analyzing research data.
Applied Multiple Regression/Correlation Analysis for Aviation Research describes and illustrates multiple regression/correlation (MRC) analysis in an aviation context and is the ideal textbook for research-oriented graduate aviation programs that require knowledge of advanced statistical strategies for analyzing research data.
Michael A. Gallo, Ph.D., is a Professor Emeritus in the College of Aeronautics at Florida Institute of Technology, USA. Ulreen O. McKinney, Ph.D. is an Associate Professor in the College of Aeronautics at Florida Institute of Technology, USA.
Inhaltsangabe
Part A Fundamental Concepts of Correlation and Regression 1. Bivariate Correlation 2. Bivariate Linear Regression Part B Establishing the Foundation of MRC 3. MRC with Two Predictors 4. MRC with More Than Two Predictors 5. Preliminary Data Screening: Regression Assumptions and Diagnostics Part C Data Analytic Strategies for MRC 6. Multiple Regression Strategies for Variable Selection 7. Analyzing Sets of Independent Variables 8. Coding Strategies for Nominal IVs Part D Additional Applications of MRC 9. Combining Nominal and Continuous IVs, ANCOVA, and Interactions 10. Other Regression Models: Mediation and Binary Logistic Regression Appendixes: A. Key Concepts in Research and Statistics B. Statistics Tables C. Answers to Part A Review Exercises
Part A Fundamental Concepts of Correlation and Regression 1. Bivariate Correlation 2. Bivariate Linear Regression Part B Establishing the Foundation of MRC 3. MRC with Two Predictors 4. MRC with More Than Two Predictors 5. Preliminary Data Screening: Regression Assumptions and Diagnostics Part C Data Analytic Strategies for MRC 6. Multiple Regression Strategies for Variable Selection 7. Analyzing Sets of Independent Variables 8. Coding Strategies for Nominal IVs Part D Additional Applications of MRC 9. Combining Nominal and Continuous IVs, ANCOVA, and Interactions 10. Other Regression Models: Mediation and Binary Logistic Regression Appendixes: A. Key Concepts in Research and Statistics B. Statistics Tables C. Answers to Part A Review Exercises
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