Stochastic Hydrology
Stochastic Hydrology. Instructor: Prof. P. P. Mujumdar, Department of Civil Engineering, IISc Bangalore. The objective of this course is to introduce the concepts of probability theory and stochastic processes with applications in hydrologic analysis and design. Modeling of hydrologic time series with specific techniques for data generation and hydrologic forecasting will be dealt with. Case study applications will be discussed.
(from nptel.ac.in )

Lecture 25 - Frequency Analysis (cont.)
VIDEO

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Introduction
Lecture 01 - Introduction
Lecture 02 - Bivariate Distributions
Lecture 03 - Independence; Functions of Random Variables
Lecture 04 - Moments of a Distribution
Commonly used Probability Distributions
Lecture 05 - Normal Distribution
Lecture 06 - Other Continuous Distributions
Data Generation
Lecture 07 - Parameter Estimation
Lecture 08 - Covariance and Correlation
Lecture 09 - Data Generation
Time Series Analysis
Lecture 10 - Time Series Analysis, Part 1
Lecture 11 - Time Series Analysis, Part 2
Lecture 12 - Time Series Analysis, Part 3
Lecture 13 - Frequency Domain Analysis
Lecture 14 - Frequency Domain Analysis (cont.), ARIMA Models
Lecture 15 - ARIMA Models, Part 2
Lecture 16 - ARIMA Models, Part 3
Lecture 17 - ARIMA Models, Part 4
Lecture 18 - Case Studies, Part 1
Lecture 19 - Case Studies, Part 2
Lecture 20 - Case Studies, Part 3
Lecture 21 - Case Studies, Part 4
Markov Chains
Lecture 22 - Markov Chains
Lecture 23 - Markov Chains (cont.)
Frequency Analysis
Lecture 24 - Frequency Analysis
Lecture 25 - Frequency Analysis (cont.)
Lecture 26 - Frequency Analysis (cont.), Probability Plotting
Lecture 27 - Probability Plotting (cont.)
Lecture 28 - Goodness of Fit
Lecture 29 - IDF Relationships
Multivariate Models
Lecture 30 - Multiple Linear Regression
Lecture 31 - Principal Component Analysis
Lecture 32 - Regression on Principal Components
Lecture 33 - Multivariate Stochastic Models, Part 1
Lecture 34 - Multivariate Stochastic Models, Part 2
Lecture 35 - Multivariate Stochastic Models, Part 3
Data Consistency
Lecture 36 - Data Consistency, Part 1
Lecture 37 - Data Consistency, Part 2
Lecture 38 - Data Consistency, Part 3
Applications and Summary
Lecture 39 - Recent Applications: Climate Change Impact Assessment
Lecture 40 - Summary