Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems.
1. Cover image - p. iv 2. Title page - p. iv 3. Table of Contents - p. iv 4. Copyright - p. iv 5. Dedication - p. v 6. Preface - p. ix 7. Chapter 1: Multivariate Data - p. ix 8. Chapter 2: R Statistical Software - p. 10 9. Chapter 3: Statistical Notions - p. 27 10. Chapter 4: Measures of Center and Variation - p. 33 11. Chapter 5: Statistical Hypothesis Testing - p. 55 12. Chapter 6: Multivariate Analysis of Variance - p. 86 13. Chapter 7: Regression Analysis - p. 112 14. Chapter 8: Principal Components - p. 132 15. Chapter 9: Factor Analysis - p. 149 16. Chapter 10: Discriminant Analysis - p. 171 17. Chapter 11: Clustering Approaches - p. 190 18. Appendix - p. 205 19. Index - p. 227
Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems.
1. Cover image - p. iv 2. Title page - p. iv 3. Table of Contents - p. iv 4. Copyright - p. iv 5. Dedication - p. v 6. Preface - p. ix 7. Chapter 1: Multivariate Data - p. ix 8. Chapter 2: R Statistical Software - p. 10 9. Chapter 3: Statistical Notions - p. 27 10. Chapter 4: Measures of Center and Variation - p. 33 11. Chapter 5: Statistical Hypothesis Testing - p. 55 12. Chapter 6: Multivariate Analysis of Variance - p. 86 13. Chapter 7: Regression Analysis - p. 112 14. Chapter 8: Principal Components - p. 132 15. Chapter 9: Factor Analysis - p. 149 16. Chapter 10: Discriminant Analysis - p. 171 17. Chapter 11: Clustering Approaches - p. 190 18. Appendix - p. 205 19. Index - p. 227
