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Last updated:

September 26, 2023

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Description

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)

Course Curriculum

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

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