# Applied Statistics and Econometrics

- Institution: IIT Kanpur
- Department: Humanities and Social Sciences
- Teacher: Prof. Deep Mukherjee
- Level: Undergraduate
- Language: English
- Subjects: Society and politics
- Source: [NPTEL](https://nptel.ac.in/courses/109104182)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/109104182)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

## Lectures

1. [Lecture 1: Introduction to Statistics](https://invisiblenetwork.ai/learn/nptel/109104182/573d2a87f884) (Video)
2. [Lecture 2: Introduction to Econometrics](https://invisiblenetwork.ai/learn/nptel/109104182/26fe8eb5dc42) (Video)
3. [Lecture 3: Organization & Presentation of Data](https://invisiblenetwork.ai/learn/nptel/109104182/5259f66145a3) (Video)
4. [Lecture 4: Summarizing Data through Descriptive Statistics](https://invisiblenetwork.ai/learn/nptel/109104182/be90e3349ccb) (Video)
5. [Lecture 5: Discrete Random Variable & Probability Distribution](https://invisiblenetwork.ai/learn/nptel/109104182/fdc60ddd2ec5) (Video)
6. [Lecture 6: Continuous Random Variables & Probability Distribution](https://invisiblenetwork.ai/learn/nptel/109104182/8305896a3824) (Video)
7. [Lecture 7: Normal Distribution](https://invisiblenetwork.ai/learn/nptel/109104182/c69ff4485030) (Video)
8. [Lecture 8: Introduction to Statistical Inference](https://invisiblenetwork.ai/learn/nptel/109104182/e2e43c922c37) (Video)
9. [Lecture 9: Estimation (Part I)](https://invisiblenetwork.ai/learn/nptel/109104182/ca6b33d8ec19) (Video)
10. [Lecture 10: Estimation (Part II)](https://invisiblenetwork.ai/learn/nptel/109104182/de859dfe2865) (Video)
11. [Lecture 11: Hypothesis Testing (Part I)](https://invisiblenetwork.ai/learn/nptel/109104182/9cb60853a1f9) (Video)
12. [Lecture 12: Hypothesis Testing (Part II)](https://invisiblenetwork.ai/learn/nptel/109104182/e558c063cded) (Video)
13. [Lecture 13: Hypothesis Testing (Part III)](https://invisiblenetwork.ai/learn/nptel/109104182/2a632f8c7b4b) (Video)
14. [Lecture 14: Hypothesis Testing (Part IV)](https://invisiblenetwork.ai/learn/nptel/109104182/da120d6754af) (Video)
15. [Lecture 15: Relationship between Qualitative Variables](https://invisiblenetwork.ai/learn/nptel/109104182/d316397a77eb) (Video)
16. [Lecture 16: Relationship Between Quantitative Variables](https://invisiblenetwork.ai/learn/nptel/109104182/3c388e68ecf2) (Video)
17. [Lecture 17: Analysis of Variance](https://invisiblenetwork.ai/learn/nptel/109104182/a81c6f19bb59) (Video)
18. [Lecture 18: One Way ANOVA](https://invisiblenetwork.ai/learn/nptel/109104182/369363d382d0) (Video)
19. [Lecture 19: Two Way ANOVA](https://invisiblenetwork.ai/learn/nptel/109104182/9a59724168cf) (Video)
20. [Lecture 20: Analysis of Covariance](https://invisiblenetwork.ai/learn/nptel/109104182/92491186ec0a) (Video)
21. [Lecture 21: Index Number (Part I)](https://invisiblenetwork.ai/learn/nptel/109104182/0354d1b72bef) (Video)
22. [Lecture 22: Index Numbers (Part II)](https://invisiblenetwork.ai/learn/nptel/109104182/dd579afc2690) (Video)
23. [Lecture 23: Classical Time Series Analysis (Part I)](https://invisiblenetwork.ai/learn/nptel/109104182/13788e3a912f) (Video)
24. [Lecture 24: Classical Time Series Analysis (Part II)](https://invisiblenetwork.ai/learn/nptel/109104182/bda7d9d6e81f) (Video)
25. [Lecture 25: Classical Linear Regression Model (Part-I)](https://invisiblenetwork.ai/learn/nptel/109104182/d5841bb7923a) (Video)
26. [Lecture 26: Classical Linear Regression Model (Part-II)](https://invisiblenetwork.ai/learn/nptel/109104182/68859c319814) (Video)
27. [Lecture 28: Hypothesis Testing with CNLRM](https://invisiblenetwork.ai/learn/nptel/109104182/4708bb4c9c23) (Video)
28. [Lecture 29: More on Hypothesis Testing and Model Specification](https://invisiblenetwork.ai/learn/nptel/109104182/9d296324e9db) (Video)
29. [Lecture 30: Violations of CLRM Assumptions (Heteroskedasticity)](https://invisiblenetwork.ai/learn/nptel/109104182/d1a34b52eb5d) (Video)
30. [Lecture 31: Violations of CLRM Assumptions (Autocorrelation and Multicollinearity)](https://invisiblenetwork.ai/learn/nptel/109104182/258ccca61f8e) (Video)
31. [Lecture 32: Time Series Regression with Stationary Data](https://invisiblenetwork.ai/learn/nptel/109104182/cf5fce428f73) (Video)
32. [Lecture 33: Time Series Regression with Non-Stationary Data](https://invisiblenetwork.ai/learn/nptel/109104182/505648d36ca9) (Video)
33. [Lecture 34: Regression with Dummy Explanatory Variable](https://invisiblenetwork.ai/learn/nptel/109104182/d9b36e2cd7e7) (Video)
34. [Lecture 35: Dummy Dependent Variable Models (Part-I)](https://invisiblenetwork.ai/learn/nptel/109104182/7651358d98fe) (Video)
35. [Lecture 36: Dummy Dependent Variable Models (Part-II)](https://invisiblenetwork.ai/learn/nptel/109104182/20aead01fe10) (Video)
36. [Lecture 37: Simultaneous Equations Model](https://invisiblenetwork.ai/learn/nptel/109104182/8a37e424a4d4) (Video)
37. [Lecture 38: Panel Data Regression](https://invisiblenetwork.ai/learn/nptel/109104182/a1ef8ba55b53) (Video)
38. [Lecture 39: Program Evaluation](https://invisiblenetwork.ai/learn/nptel/109104182/4682f9caaffe) (Video)
39. [Lecture 40: Data Analysis and Regression with R](https://invisiblenetwork.ai/learn/nptel/109104182/d78e7ecfabb0) (Video)
40. [Lecture 41: Regression Involving Dummy Variables in R](https://invisiblenetwork.ai/learn/nptel/109104182/554249997cce) (Video)
41. [Lecture 42: Time Series Analysis in R](https://invisiblenetwork.ai/learn/nptel/109104182/b59a919071f2) (Video)
42. [Live Session 10-02-2024](https://invisiblenetwork.ai/learn/nptel/109104182/573d2a87f884-2) (Video)