# Engineering Statistics

- Institution: IIT Bombay
- Department: Multidisciplinary
- Teacher: Prof. Manjesh Hanawal
- Level: Undergraduate
- Language: English
- Subjects: Mathematics, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/127101233)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/127101233)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

## Lectures

1. [Lecture 1: Introduction to Probability](https://invisiblenetwork.ai/learn/nptel/127101233/6496f8bd0f8d) (Video)
2. [Lecture 2: Consequences of Axioms](https://invisiblenetwork.ai/learn/nptel/127101233/d924a41e686c) (Video)
3. [Lecture 3: Interpretation of Probability](https://invisiblenetwork.ai/learn/nptel/127101233/eb7c3a8fbf21) (Video)
4. [Lecture 4: Total Probability law and Baye’s Theorem I](https://invisiblenetwork.ai/learn/nptel/127101233/4f9217780d83) (Video)
5. [Lecture 5: Total Probability law and Baye’s Theorem II](https://invisiblenetwork.ai/learn/nptel/127101233/60ff20e86903) (Video)
6. [Lecture 6: Random variables and Cumulative Density Function](https://invisiblenetwork.ai/learn/nptel/127101233/e25f3c499cc6) (Video)
7. [Lecture 7: Discrete and Continuous random variables I](https://invisiblenetwork.ai/learn/nptel/127101233/3f9a54bf5e97) (Video)
8. [Lecture 8: Discrete and Continuous random variables II](https://invisiblenetwork.ai/learn/nptel/127101233/5681af56b848) (Video)
9. [Lecture 9: Expectation and Variance](https://invisiblenetwork.ai/learn/nptel/127101233/5bb58ffcc140) (Video)
10. [Lecture 10: Function of Random variables](https://invisiblenetwork.ai/learn/nptel/127101233/79a46822763a) (Video)
11. [Lecture 11: Generating RVs, Joint Distribution of RVs](https://invisiblenetwork.ai/learn/nptel/127101233/a7ac5cd24b2a) (Video)
12. [Lecture 12: Joint Distribution of RVs and Marginal densities](https://invisiblenetwork.ai/learn/nptel/127101233/c17891c467c8) (Video)
13. [Lecture 13: Covariance of Random variables](https://invisiblenetwork.ai/learn/nptel/127101233/25023dd6330c) (Video)
14. [Lecture 14: Moment Generating Functions](https://invisiblenetwork.ai/learn/nptel/127101233/7571c839e646) (Video)
15. [Lecture 15: Conditional PMF and PDF](https://invisiblenetwork.ai/learn/nptel/127101233/f1933624e62f) (Video)
16. [Lecture 16: Law of Large numbers, Central Limit Theorem](https://invisiblenetwork.ai/learn/nptel/127101233/ba4f5801a2da) (Video)
17. [Lecture 17: Application of Central Limit Theorem I](https://invisiblenetwork.ai/learn/nptel/127101233/e16930740c22) (Video)
18. [Lecture 18: Application of Central Limit Theorem II](https://invisiblenetwork.ai/learn/nptel/127101233/7b3ade66ea6b) (Video)
19. [Lecture 19: Gamma and Chisquare distributions](https://invisiblenetwork.ai/learn/nptel/127101233/3ae74b46b71f) (Video)
20. [Lecture 20: Beta distributions and Exponential families](https://invisiblenetwork.ai/learn/nptel/127101233/31e1a09790bc) (Video)
21. [Lecture 21: Random Sampling, Sample mean and Sample variance](https://invisiblenetwork.ai/learn/nptel/127101233/2f4ccd6a62fc) (Video)
22. [Lecture 22: Sampling from Gaussian distribution and t distribution](https://invisiblenetwork.ai/learn/nptel/127101233/60b637452a79) (Video)
23. [Lecture 23: Student’s t distribution](https://invisiblenetwork.ai/learn/nptel/127101233/9eefb78fa2e1) (Video)
24. [Lecture 24: Fdistribution and its properties](https://invisiblenetwork.ai/learn/nptel/127101233/99fd785ec835) (Video)
25. [Lecture 25: Convergence of Random variables and Consistency](https://invisiblenetwork.ai/learn/nptel/127101233/d74a98b91dd0) (Video)
26. [Lecture 26: Order statistics, Median and Percentiles](https://invisiblenetwork.ai/learn/nptel/127101233/b8cf286b6c57) (Video)
27. [Lecture 27: Generating random sample Direct method](https://invisiblenetwork.ai/learn/nptel/127101233/dbce5b3a44ef) (Video)
28. [Lecture 28: Generating random sample Indirect method](https://invisiblenetwork.ai/learn/nptel/127101233/c1d70e7fa1d7) (Video)
29. [Lecture 29: Introduction to python](https://invisiblenetwork.ai/learn/nptel/127101233/13f415b531ee) (Video)
30. [Lecture 30: Python Loops and Numpy library](https://invisiblenetwork.ai/learn/nptel/127101233/d6fc1d600565) (Video)
31. [Lecture 31: Sufficiency Principles and Sufficient Statistics](https://invisiblenetwork.ai/learn/nptel/127101233/afa5ca1327b1) (Video)
32. [Lecture 32: Sufficient Statistics and Characterizatio n of Sufficient Statistics](https://invisiblenetwork.ai/learn/nptel/127101233/94dafee1b332) (Video)
33. [Lecture 33: Characterizatio n of Sufficient Statistics and Factorization Theorem](https://invisiblenetwork.ai/learn/nptel/127101233/f6d06dd3d99f) (Video)
34. [Lecture 34: Example of Factorization Theorem, Minimal Sufficient Statistics](https://invisiblenetwork.ai/learn/nptel/127101233/92c5b0c9b5d6) (Video)
35. [Lecture 35: Minimal sufficient statistics](https://invisiblenetwork.ai/learn/nptel/127101233/3039befe4b8f) (Video)
36. [Lecture 36: Test for minimal sufficient statistics with examples, Ancillary Statistics](https://invisiblenetwork.ai/learn/nptel/127101233/dde8a33cfc8c) (Video)
37. [Lecture 37: Likelihood Functions, Maximum Likelihood Estimator](https://invisiblenetwork.ai/learn/nptel/127101233/0b5daf1369e3) (Video)
38. [Lecture 38: Method of moments, Baye’s Estimator](https://invisiblenetwork.ai/learn/nptel/127101233/2e8f126b1b13) (Video)
39. [Lecture 39: Evaluating Estimator, Cramer Rao Bound, Fisher Information](https://invisiblenetwork.ai/learn/nptel/127101233/ff49570befae) (Video)
40. [Lecture 40: Evaluating Estimator, Cramer Rao Bound, Fisher Information (Contd.)](https://invisiblenetwork.ai/learn/nptel/127101233/76c76ea2fd9a) (Video)
41. [Lecture 41: Hypothesis Testing, Likelihood Ratio Test](https://invisiblenetwork.ai/learn/nptel/127101233/ef71de5ba12e) (Video)
42. [Lecture 42: Hypothesis Testing, Bayes Test](https://invisiblenetwork.ai/learn/nptel/127101233/ca647e8ec5b6) (Video)
43. [Lecture 43: Type I and II errors, Power Functions](https://invisiblenetwork.ai/learn/nptel/127101233/b3c99b00d19c) (Video)
44. [Lecture 44: Type I and II errors, Power Functions (Contd.)](https://invisiblenetwork.ai/learn/nptel/127101233/ee1b76c3dc06) (Video)
45. [Lecture 45: Calculations of Power Functions](https://invisiblenetwork.ai/learn/nptel/127101233/58e17ec70a14) (Video)
46. [Lecture 46: Unbiased Test, Uniformly Most Powerful Test, Neyman Pearson Lemma, Interval Estimation](https://invisiblenetwork.ai/learn/nptel/127101233/6e17ed762ff6) (Video)
47. [Lecture 47: Interval Estimation](https://invisiblenetwork.ai/learn/nptel/127101233/77bf082f755e) (Video)
48. [Lecture 48: Interval Estimation (Contd.)](https://invisiblenetwork.ai/learn/nptel/127101233/ddd15a3bcf50) (Video)
49. [Lecture 49: Constructiong Confidence Intervals from tests](https://invisiblenetwork.ai/learn/nptel/127101233/d82389ea20ba) (Video)
50. [Lecture 50: Python numpy and pandas functions II](https://invisiblenetwork.ai/learn/nptel/127101233/42b5fa034a7c) (Video)
51. [Lecture 51: Tutology of tests and confidence intervals](https://invisiblenetwork.ai/learn/nptel/127101233/567039d4bc80) (Video)
52. [Lecture 52: Tutology of tests and confidence intervals (Contd.)](https://invisiblenetwork.ai/learn/nptel/127101233/28ed7bb61557) (Video)
53. [Lecture 53: pvalue, ptest of significance of a statistical test](https://invisiblenetwork.ai/learn/nptel/127101233/3a3596588c6e) (Video)
54. [Lecture 54: ttest & Ftest, ANOVA](https://invisiblenetwork.ai/learn/nptel/127101233/630c52794544) (Video)
55. [Lecture 55: Nonparametric test, Goodness of fit, Chi squared test](https://invisiblenetwork.ai/learn/nptel/127101233/ec50ed59b834) (Video)
56. [Lecture 56: Distribution of Chisquared test statistics](https://invisiblenetwork.ai/learn/nptel/127101233/098c4a81f653) (Video)
57. [Lecture 57: Kolmogrov Smirnov test](https://invisiblenetwork.ai/learn/nptel/127101233/37a7052d6c07) (Video)
58. [Lecture 58: Lilliefors’s test and Explorator Data Analysis, QQ Plot and P P Plot](https://invisiblenetwork.ai/learn/nptel/127101233/340cb43d4396) (Video)
59. [Lecture 59: Generating random samples using Python, Hypothesis Testing using Python](https://invisiblenetwork.ai/learn/nptel/127101233/9dd4916171d4) (Video)
60. [Lecture 60: Generating random samples using Python, Hypothesis Testing using Python (Contd.)](https://invisiblenetwork.ai/learn/nptel/127101233/503b14d307bd) (Video)
61. [Live Session 19-03-2024](https://invisiblenetwork.ai/learn/nptel/127101233/6496f8bd0f8d-2) (Video)
62. [Live Session 16-04-2024](https://invisiblenetwork.ai/learn/nptel/127101233/d924a41e686c-2) (Video)