Introduction to Statistics Course | IIT Hyderabad | NPTEL | Prof. Sameen Naqvi
Course Details
| Exam Registration | 151 |
|---|---|
| Course Status | Ongoing |
| Course Type | Core |
| Language | English |
| Duration | 12 weeks |
| Categories | Mathematics |
| Credit Points | 3 |
| Level | Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 18 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Master Data with IIT Hyderabad's Introduction to Statistics Course
In our data-driven world, the ability to collect, analyze, and interpret data is no longer a niche skill—it's a fundamental requirement across science, engineering, and business. If you're looking to build a strong, practical foundation in statistical methods, the Introduction to Statistics course from the Indian Institute of Technology Hyderabad (IIT Hyderabad) is your perfect starting point. This comprehensive 12-week postgraduate program, available through NPTEL, is meticulously designed to transform raw data into actionable insights.
Your Expert Guide: Prof. Sameen Naqvi
Learning from the best makes all the difference. This course is led by Prof. Sameen Naqvi, an accomplished Assistant Professor in the Department of Mathematics at IIT Hyderabad. With a doctorate from IIT Kanpur and post-doctoral research experience at prestigious institutions like The Chinese University of Hong Kong, Prof. Naqvi brings a wealth of knowledge to the classroom.
Her expertise in Reliability Theory, Applied Statistics, and Stochastic Orders ensures the course content is both rigorous and relevant. As an active researcher supervising PhD students and numerous undergraduate projects, she connects theoretical concepts to real-world applications, providing students with a learning experience grounded in academic excellence and practical insight.
Who Should Take This Course?
This course is ideally suited for:
- Intended Audience: Undergraduate and postgraduate students from Science and Engineering streams.
- Prerequisites: Learners should be pursuing an undergraduate degree and have completed a foundational course in Probability. A recommended prerequisite is the NPTEL course Probability and Statistics.
- Industry Support: The skills taught are highly valued by top-tier companies including Goldman Sachs, Microsoft, Adobe, Flipkart, Samsung R&D, and Salesforce, highlighting the direct career relevance of the curriculum.
What Will You Learn? A 12-Week Journey
The course is structured to guide you through the entire data analysis pipeline, from raw data to confident conclusions. Here’s a detailed week-by-week breakdown:
| Week | Topic | Key Learning Outcome |
|---|---|---|
| 1 | Collecting Data | Understand methodologies and principles for robust data collection. |
| 2 | Summarizing Data | Learn descriptive statistics to summarize data sets effectively. |
| 3 | Visualizing Data | Master techniques to create informative graphs and charts for different data types. |
| 4 | Sampling Distribution (One Sample) | Grasp the foundational concept of sampling distributions for mean, variance, and proportion. |
| 5 | Sampling Distribution (Two Sample) | Extend understanding to compare two populations. |
| 6 | Point Estimation | Learn methods to calculate single-value estimates for population parameters. |
| 7 | Point Estimation for Missing Data | Tackle real-world data imperfections and learn estimation techniques for incomplete datasets. |
| 8 & 9 | Testing of Hypothesis | Dive deep into formulating and testing hypotheses about population means, variances, and proportions. |
| 10 | Bootstrap Hypothesis Testing | Explore modern resampling techniques for hypothesis testing. |
| 11 | Confidence Interval Estimation | Learn to estimate a range of plausible values for population parameters. |
| 12 | Bootstrap Confidence Interval | Apply bootstrap methods to construct confidence intervals, a key modern statistical tool. |
Essential Learning Resources
To supplement the video lectures and assignments, the course recommends several authoritative textbooks, ensuring you have access to multiple perspectives and in-depth explanations:
- Ross, S.M. (2014). Introduction to Probability and Statistics for Engineers and Scientists.
- Rohatgi, V.K. and Saleh, A.M.E. (2015). An Introduction to Probability and Statistics.
- Montgomery, D.C. and Runger, G.C. (2010). Applied Statistics and Probability for Engineers.
- Hogg, R.V. and Craig, A.T. (1995). Introduction to Mathematical Statistics.
- Walpole, R.E., et al. (1993). Probability and Statistics for Engineers and Scientists.
- Efron, B. and Tibshirani, R.J. (1994). An introduction to the bootstrap.
Why Enroll in This Introduction to Statistics Course?
This course is more than just a series of lectures; it's a structured pathway to statistical fluency. By combining theoretical foundations (like probability and sampling distributions) with practical analysis techniques (like estimation and hypothesis testing), it builds a complete skill set. The inclusion of modern topics like bootstrap methods ensures you learn both classical and contemporary statistical tools.
Whether you aim to enhance your academic research, prepare for advanced studies, or boost your employability in data-centric roles, this course provides the critical knowledge and skills demanded by today's top industries. Take the first step towards mastering the language of data with expert guidance from IIT Hyderabad.
Ready to decode data? Explore this course on the NPTEL platform and enroll to start your statistical journey.
Enroll Now →