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Foundational Level Course

Statistics for Data Science II

This second course will develop on the first course on statistics and further delve into the main statistical problems and solution approaches

Code BSMA1004
Credits 4 Credits
Type Foundational
Prerequisites None
Core Competencies

What You'll Learn

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  • Recalling statistical modeling, description of data.

  • Applying Probability distributions and related concepts to the data sets

  • Explaining the concept of estimation of parameters.

  • Solving the problems related to point and interval estimation.

  • Explaining the concept of Testing of hypothesis related to mean and variance

  • Analysing the data using simple regression models and setting up relevant hypothesis tests

12-Week Roadmap

Course Structure & Syllabus

For details of standard term assessment timelines and exam structures, visit our Academics page.

WEEK 1
Multiple random variables - Two random variables, Multiple random variables and distributions
WEEK 2
Multiple random variables - Independence, Functions of random variables - Visualization, functions of multiple random variables
WEEK 3
Expectations Casino math, Expected value of a random variable, Scatter plots and spread, Variance and standard deviation, Covariance and correlation, Inequalities
WEEK 4
Continuous random variables Discrete vs continuous, Weight data, Density functions, Expectations
Supplementary Learning Materials

Reference Documents & Notes

Joint Discrete Distributions (VOL 1)

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Joint Continuous Distributions (VOL 2)

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Reading List

Prescribed Books & References

  • Probability and Statistics with Examples using R. Author: Siva Athreya, Deepayan Sarkar and Steve Tanner
Faculty & Experts

About the Instructors

Andrew Thangaraj

Andrew Thangaraj

Professor , Electrical Engineering Department , IIT Madras

Andrew Thangaraj received his B. Tech in Electrical Engineering from the Indian Institute of Technology (IIT) Madras in 1998 and Ph.D. in Electrical Engineering from the Georgia Institute of Technology, Atlanta, USA in 2003.

He was a post-doctoral researcher at the GTL-CNRS Telecom lab at Georgia Tech Lorraine, Metz, France from Aug 2003 till May 2004. Since 2004, he has been a faculty at the Department of Electrical Engineering, IIT Madras, where he is currently a professor.

His research interests are in the broad areas of information theory, error-control coding and information-theoretic aspects of cryptography. From Jan 2012 till Jan 2018, he served as Editor for the IEEE Transactions on Communications. From July 2018, he is an Associate Editor for the IEEE Transactions on Information Theory.

From Nov 2011, he has been one of the NPTEL coordinators for IIT Madras. At NPTEL, he has played a key role in the starting of online courses and certification. He is currently a National MOOCs coordinator for NPTEL under the SWAYAM project of the MHRD.

Prof. Andrew is also one of the coordinators for the IIT Madras Online BSc Degree Program, which was launched in June, 2020.