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Course12710601120 lectures

Statistical Data Analysis: Application to Atmospheric Science

Prof. Sarita Azad · IIT Mandi

Start with lecture 1 At NPTEL

About

Statistical Data Analysis: Applications to Atmospheric Science provides a comprehensive introduction to data analytics through theory and hands-on practice. The course covers data classification, descriptive and inferential statistics, and exploratory data analysis.

Learners will develop skills in visualization, trend analysis, stochastic modeling, and forecasting techniques. It also introduces multivariate methods such as regression, clustering, Principal Component Analysis (PCA), and Self-Organizing Maps (SOM/Kohonen Maps).

Every concept is supported through practical implementation using Python code provided to learners. Although the examples are drawn primarily from climate and atmospheric datasets, the methods are broadly applicable across disciplines.

Intended audience: UG/PG/PhD all disciplines

Lectures

Week 1

  1. Introduction to Data Analytics -I YouTube
  2. Introduction to Data Analytics -II YouTube
  3. Introduction to Data Analytics -III YouTube
  4. Introduction to Data Analytics- IV YouTube
  5. Statistical Data Analysis- Case study on Himalayan climate data YouTube

Week 2

  1. Introduction to Statistics YouTube
  2. Fundamentals of Probability DIstribution YouTube
  3. Probability Distributions for Time Series Prediction-I YouTube
  4. Probability Distributions for Time Series Prediction-II YouTube
  5. Statistical Data Analysis- Case study on Himalayan Pollution Data YouTube

Week 3

  1. Time Series Forecasting-I YouTube
  2. Time Series Forecasting -II YouTube
  3. Time Series Forecasting-III YouTube
  4. Time Series Forecasting- IV YouTube
  5. Case study: decline of SO4 and its role in Himalayan warming YouTube

Week 4

  1. K-means Clustering YouTube
  2. K-means clustering cont. YouTube
  3. Introduction to PCA YouTube
  4. Self-organizing Maps YouTube
  5. Self-organizing Maps Cont. YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Mandi
Department
Multidisciplinary
Teacher
Prof. Sarita Azad
Level
Undergraduate
Language
English
Subjects
Mathematics, Earth and environment
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
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