Qualifier Applications for the second batch are now open.   

Qualifier Applications for the second batch are now open.   

Foundational Level Course

Statistics for Data Science I

The students will be introduced to large datasets. Using this data, the students will be introduced to various insights one can glean from the data. Basic concepts of probability also will be introduced during the course leading to a discussion on Random variables.

by Usha Mohan

Course ID: BSCMA1002

Course Credits: 4

Course Type: Foundational

Prerequisites: None

What you’ll learn

Create, download, manipulate, and analyse data sets.
Frame questions that can be answered from data in terms of variables and cases.
Describe data using numerical summaries and visual representations.
Estimate chance by applying laws of probability.
Translate real-world problems into probability models.
Calculating expectation and variance of a random variable.
Describe and apply the properties of the Binomial Distribution and Normal distribution.

Course structure & Assessments

12 weeks of coursework, weekly online assignments, 3 in-person invigilated quizzes, 1 in-person invigilated end term exam. For details of standard course structure and assessments, visit Academics page.

WEEK 1 - Click Here Introduction and motivation for statistics
WEEK 2 Descriptive Statistics - Organisation and visualisation of data
WEEK 3 Descriptive Statistics - Numerical Summaries
WEEK 4 Descriptive Statistics - Association between variables
WEEK 5 Permutations and combinations
WEEK 6 Probability Introduction
WEEK 7 Conditional Probability
WEEK 8 Discrete Random Variables
WEEK 9 Discrete Random Variables (Continued)
WEEK 10 Binomial Distribution
WEEK 11 Normal Distribution
WEEK 12 Normal Distribution (Continued)

Prescribed Books

The following are the suggested books for the course:

Introductory Statistics (10th Edition) - ISBN 9780321989178, by Neil A. Weiss published by Pearson

Introductory Statistics (4th Edition) - by Sheldon M. Ross

About the Instructors

Usha Mohan
Professor, Management Studies, IIT Madras

Usha Mohan holds a Ph.D. from Indian Statistical Institute. She has worked as a researcher in ISB Hyderabad and Lecturer at University of Hyderabad prior to joining IIT Madras. She offers courses in Data analytics, Operations research, and Supply chain management to under graduate, post graduate and doctoral students. In addition, she conducts training in Optimization methods and Data Analytics for industry professionals. Her research interests include developing quantitative models in operations management and combinatorial optimization.