Lecture notes

Chapter0: Vector and Matrix (fuel for gap)

Chapter1: Basic concepts and notions

Chapter2: Regression analysis and an example of coreelation test

Chapter3:Filtering and Spectrum analysis and Digital Filter

Chapter4: Linear multivariate statistical analysis - I

Chapter5: Linear multivariate statistical analysis - II

Chapter6: Nonlinear Regression - Neural Network approach

Chapter7: Nonlinear multivariate statistical analysis

Chapter8: Estimation of potential predictability

Chapter9: Ensemble-based Data assimilation methods

Extra readings

Review paper on Nonlinear multivariate statistical analysis (William Heish)

Statistical Methods in the Atmospheric Sciences (Reference book)

Prediction Verification (Reference book)