# Statistical Foundation for Big Data Analysis

- Institution: IIT Kharagpur
- Department: Computer Science and Engineering
- Teacher: Prof. Arindam Banerjee
- Level: Undergraduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106105848)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106105848)
- 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 : Big Data : Definition, Examples and Challenges](https://invisiblenetwork.ai/learn/nptel/106105848/1794afbffcf4) (Video)
2. [Lecture 2 : Big Data Analysis vs Big Data Processing : Role of Dimensional Statistics.](https://invisiblenetwork.ai/learn/nptel/106105848/2756c89cb564) (Video)
3. [Lecture 3 : Statistical Framework 1](https://invisiblenetwork.ai/learn/nptel/106105848/cd9cf65e96a1) (Video)
4. [Lecture 4 : Statistical Framework 2](https://invisiblenetwork.ai/learn/nptel/106105848/fd66c9d6c296) (Video)
5. [Lecture 5 : Statistical Framework 3](https://invisiblenetwork.ai/learn/nptel/106105848/9048d53dc362) (Video)
6. [Lecture 06 : Point Estimation: Unbiased Estimation](https://invisiblenetwork.ai/learn/nptel/106105848/1ea047d78c7f) (Video)
7. [Lecture 07 : Point Estimation: Likelihood 1](https://invisiblenetwork.ai/learn/nptel/106105848/83ceaaa4de17) (Video)
8. [Lecture 08 : Point Estimation: Likelihood 2](https://invisiblenetwork.ai/learn/nptel/106105848/8735880d9231) (Video)
9. [Lecture 09 : Method of Moments](https://invisiblenetwork.ai/learn/nptel/106105848/b76aee1c9913) (Video)
10. [Lecture 10 : Point Estimation: Asymptotics](https://invisiblenetwork.ai/learn/nptel/106105848/c576e7c24f0e) (Video)
11. [Lecture 11 :Interval Estimation 1](https://invisiblenetwork.ai/learn/nptel/106105848/b4b7796d4d04) (Video)
12. [Lecture 12 : Interval Estimation 2](https://invisiblenetwork.ai/learn/nptel/106105848/fa42d25d2b95) (Video)
13. [Lecture 13 : Basics of Hypothesis Testing-I](https://invisiblenetwork.ai/learn/nptel/106105848/38e5e849ff2b) (Video)
14. [Lecture 14 : Basics of Hypothesis Testing-II](https://invisiblenetwork.ai/learn/nptel/106105848/f2baa3663f01) (Video)
15. [Lecture 15 : Basics of Hypothesis Testing-lll](https://invisiblenetwork.ai/learn/nptel/106105848/afdd5745777c) (Video)
16. [Lecture 16 :Bias Variance and Mean Squared Errors](https://invisiblenetwork.ai/learn/nptel/106105848/11358def008e) (Video)
17. [Lecture 17 :Bias Variance and Mean Squared Errors](https://invisiblenetwork.ai/learn/nptel/106105848/6d2bd4410bd6) (Video)
18. [Lecture 18 :Bias Variance and Mean Squared Errors](https://invisiblenetwork.ai/learn/nptel/106105848/6a6aa0dde420) (Video)
19. [Lecture 19 :Bias Variance and Mean Squared Errors](https://invisiblenetwork.ai/learn/nptel/106105848/4554380614ab) (Video)
20. [Lecture 20 : Bias Variance and Mean Squared Errors](https://invisiblenetwork.ai/learn/nptel/106105848/decb05ca1e83) (Video)
21. [Lecture 21 : Bias Variance Decomposition](https://invisiblenetwork.ai/learn/nptel/106105848/2238d34f87f0) (Video)
22. [Lecture 22 : Cross Validation and Bias Variance Tradeoff](https://invisiblenetwork.ai/learn/nptel/106105848/964b86748c1a) (Video)
23. [Lecture 23 : Methods of Cross Validation](https://invisiblenetwork.ai/learn/nptel/106105848/373be418b45b) (Video)
24. [Lecture 24 : Regression vs Classification](https://invisiblenetwork.ai/learn/nptel/106105848/ab26812ca2ec) (Video)
25. [Lecture 25 : Inference on Logistic Regression](https://invisiblenetwork.ai/learn/nptel/106105848/7be297ee323a) (Video)
26. [Lecture 26 : Regression: Linear Regression](https://invisiblenetwork.ai/learn/nptel/106105848/5e59fc1876eb) (Video)
27. [Lecture 27 : Regression: Linear Regression 2](https://invisiblenetwork.ai/learn/nptel/106105848/379bdaf5d619) (Video)
28. [Lecture 28 : Regression: Multiple Linear Regression 1](https://invisiblenetwork.ai/learn/nptel/106105848/c52295b1fcd4) (Video)
29. [Lecture 29 : Regression: Multiple Linear Regression 2](https://invisiblenetwork.ai/learn/nptel/106105848/7a58065132b4) (Video)
30. [Lecture 30 : Regression: Multiple Linear Regression 3](https://invisiblenetwork.ai/learn/nptel/106105848/0169b1359a97) (Video)
31. [Lecture 31 : Generalities of Multivariate Distribution](https://invisiblenetwork.ai/learn/nptel/106105848/5e33063771a8) (Video)
32. [Lecture 32 : Bivariate Normal Distribution](https://invisiblenetwork.ai/learn/nptel/106105848/4f7f90b3524f) (Video)
33. [Lecture 33 : Multivariate Normal Distribution 1](https://invisiblenetwork.ai/learn/nptel/106105848/e2b5fa4f1df5) (Video)
34. [Lecture 34 : Multivariate Normal Distribution 2](https://invisiblenetwork.ai/learn/nptel/106105848/2b2f6e372eae) (Video)
35. [Lecture 35 : Multivariate Normal Distribution 3](https://invisiblenetwork.ai/learn/nptel/106105848/89f60adba423) (Video)
36. [Lecture 36 : Supervised Learning vs Unsupervised Learning](https://invisiblenetwork.ai/learn/nptel/106105848/5c75ecc50201) (Video)
37. [Lecture 37 : Heirarchical Clustering](https://invisiblenetwork.ai/learn/nptel/106105848/beb567ea68a5) (Video)
38. [Lecture 38 : K-means clustering](https://invisiblenetwork.ai/learn/nptel/106105848/f77ff05907c0) (Video)
39. [Lecture 39 : Curse of Dimensionality](https://invisiblenetwork.ai/learn/nptel/106105848/8458e38a3fd7) (Video)
40. [Lecture 40 : Behaviour of Volume in High Dimension](https://invisiblenetwork.ai/learn/nptel/106105848/c2e872a06f05) (Video)
41. [Lecture 41 : Introduction to Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/c0ffbfa13d94) (Video)
42. [Lecture 42 : Eigenvalues and Eigenvectors](https://invisiblenetwork.ai/learn/nptel/106105848/d84f456649e4) (Video)
43. [Lecture 43 : Mathematical Formulation of Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/52c8080521d0) (Video)
44. [Lecture 44 : Mathematical Foundation of Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/5a8d3787a5f3) (Video)
45. [Lecture 45 : Population Principal Component Analysis for Normal Distribution](https://invisiblenetwork.ai/learn/nptel/106105848/92353933ca71) (Video)
46. [Lecture 46 : Population vs Sample Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/220b687dd6c3) (Video)
47. [Lecture 47 : Mathematical Formulation of Sample PCA](https://invisiblenetwork.ai/learn/nptel/106105848/54eed2dd0b9f) (Video)
48. [Lecture 48 : Sample PCA for Covariance matrix and Correlation Matrix](https://invisiblenetwork.ai/learn/nptel/106105848/3355ee6669a4) (Video)
49. [Lecture 49 : Examples of Sample PCA](https://invisiblenetwork.ai/learn/nptel/106105848/c69256a4180c) (Video)
50. [Lecture 50 : Inference on Principal Component Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/e8155e65344e) (Video)
51. [Lecture 51 : Network Data and Random Graph](https://invisiblenetwork.ai/learn/nptel/106105848/5effe93c3124) (Video)
52. [Lecture 52 : Properties of Random Graph](https://invisiblenetwork.ai/learn/nptel/106105848/19db7b06310f) (Video)
53. [Lecture 53 : Law of Large Numbers for Random Graph 1](https://invisiblenetwork.ai/learn/nptel/106105848/5a0a990c7e51) (Video)
54. [Lecture 54 : Law of Large Numbers for Random Graph 2](https://invisiblenetwork.ai/learn/nptel/106105848/af28b3772384) (Video)
55. [Lecture 55 : Law of Large Numbers for Random Graph 3](https://invisiblenetwork.ai/learn/nptel/106105848/f68efbe7db3f) (Video)
56. [Lecture 56 : Introduction to Network Medicine](https://invisiblenetwork.ai/learn/nptel/106105848/d8fda5fbba23) (Video)
57. [Lecture 57 :Selected Case Study on Network Medicine](https://invisiblenetwork.ai/learn/nptel/106105848/7f80675f6434) (Video)
58. [Lecture 58 : Social Network Analysis](https://invisiblenetwork.ai/learn/nptel/106105848/4cfdf429d90a) (Video)
59. [Lecture 59 : Simple Linear Regression on Social Network Data](https://invisiblenetwork.ai/learn/nptel/106105848/a0df5faf8d25) (Video)
60. [Lecture 60 : Conclusion and Course Summary](https://invisiblenetwork.ai/learn/nptel/106105848/ea101d196a9f) (Video)