- Provides a strong, yet concise, introduction to applied statistics that is specific to atmospheric science- Contains revised and expanded sections on nonparametric tests, test multiplicity and quality uncertainty descriptors- Includes new sections on ANOVA, quantile regression, the lasso and other regularization methods, regression trees, changepoint detection, ensemble forecasting and exponential smoothing
1. Introduction 2. Review of Probability 3. Empirical Distributions and Exploratory Data Analysis 4. Parametric Probability Distributions 5. Frequentist Statistical Inference 6. Bayesian Inference 7. Statistical Forecasting 8. Ensemble Forecasting 9. Forecast Verification 10. Time Series 11. Matrix Algebra and Random Matrices 12. Multivariate Normal Distribution 13. Principal Component (EOF) Analysis 14. Linear multivariate analysis of vector pairs: CCA, MCA, and RA 15. Discrimination and Classification 16. Cluster Analysis
Daniel S. Wilks has been a member of the Atmospheric Sciences faculty at Cornell University since 1987, and is the author of Statistical Methods in the Atmospheric Sciences (2011, Academic Press), which is in its third edition and has been continuously in print since 1995. Research areas include statistical forecasting, forecast postprocessing, and forecast evaluation.