Modules / Lectures


Sl.No Chapter Name MP4 Download
1Lecture 01: Overview of Module 01 & Introduction of CausalityDownload
2Lecture 02: Correlation and CausalityDownload
3Lecture 03: Correlation and Causality (Contd.)Download
4Lecture 04: Correlation and Causality (Contd.)Download
5Lecture 05: Probability TheoryDownload
6Lecture 06: Probability Theory (Contd.)Download
7Lecture 07: Probability Theory (Contd.)Download
8Lecture 08: Probability Theory (Contd.)Download
9Lecture 09: Posterior ProbabilityDownload
10Lecture 10: Bayesian TheoremDownload
11Lecture 11: Bayesian Theorem (Contd.): Repeated TrialDownload
12Lecture 12: Bayesian Theorem (Contd.): Example of Diamond IdentificationDownload
13Lecture 13: Probability DistributionDownload
14Lecture 14: Double Structure of VariableDownload
15Lecture 15: Probability Distribution (Discrete/Continuous Variable) Random VariableDownload
16Lecture 16: Probability Mass Function (PMF) Probability Density Function (PDF)"Download
17Lecture 17: Expectation, Variance, CovarianceDownload
18Lecture 18: Expectation, Variance, Covariance (Contd.)Download
19Lecture 19: Covariance RuleDownload
20Lecture 20: Bernoulli DistributionDownload
21Lecture 21: Bernoulli Distribution (Contd.)Download
22Lecture 22: Normal Approximation of Bernoulli DistributionDownload
23Lecture 23: SamplingDownload
24Lecture 24: Sampling (Contd.)Download
25Lecture 25: Central Limit TheoremDownload
26Lecture 26: Law of Large Numbers LLNDownload
27Lecture 27: Properties of EstimatorDownload
28Lecture 28: Conflict Between Unbiasedness and Min VarianceDownload
29Lecture 29: T - DistributionDownload
30Lecture 30: Normal DistributionDownload
31Lecture 31: Normal Distribution (Contd.)Download
32Lecture 32: Hypothesis TestingDownload
33Lecture 33: Decision RulesDownload
34Lecture 34: Level of SignificanceDownload
35Lecture 35: P ValueDownload
36Lecture 36: Power of a TestDownload
37Lecture 37: Confidence IntervalDownload
38Lecture 38: Confidence Interval ExampleDownload
39Lecture 39: Properties of Power of a TestDownload
40Lecture 40: Introduction to Module IIDownload
41Lecture 41: Error Term, Coefficient of Determination, Regression CoefficientDownload
42Lecture 42: Error Term, Coefficient of Determination, Regression Coefficient (Contd.)Download
43Lecture 43: Error Term, Coefficient of Determination, Regression Coefficient (Contd.)Download
44Lecture 44: Definition : Variable, Parameter and CoefficientDownload
45Lecture 45: Introduction to Regression: Recapitulating Correlation and Causal ThinkingDownload
46Lecture 46: Adjusted R-SquaredDownload
47Lecture 47: Degrees of FreedomDownload
48Lecture 48: Multiple RegressionDownload
49Lecture 49: Multiple Regression (Contd.)Download
50Lecture 50: Regression TableDownload
51Lecture 51: Regression Table (Contd.)Download
52Lecture 52: MulticollinearityDownload
53Lecture 53: Multicollinearity (Contd.)Download
54Lecture 54: Multicollinearity (Contd.)Download
55Lecture 55: Multicollinearity (Contd.)Download
56Lecture 56: Multicollinearity (Contd.)Download
57Lecture 57: Dummy VariableDownload
58Lecture 58: Dummy variable (Contd.)Download
59Lecture 59: Dummy variable (Contd.)Download
60Lecture 60: Dummy variable (Contd.)Download
61Lecture 61: Dummy variable (Contd.)Download
62Lecture 62: Dummy variable (Contd.)Download
63Lecture 63: Dummy variable (Contd.)Download
64Lecture 64: HeteroscedasticityDownload
65Lecture 65: Heteroscedasticity (Contd.)Download
66Lecture 66 : Heteroscedasticity (Contd.)Download
67Lecture 67 : Heteroscedasticity (Contd.)Download
68Lecture 68 : Heteroscedasticity (Contd.)Download
69Lecture 69 : Heteroscedasticity (Contd.)Download

Sl.No Chapter Name English
1Lecture 01: Overview of Module 01 & Introduction of CausalityPDF unavailable
2Lecture 02: Correlation and CausalityPDF unavailable
3Lecture 03: Correlation and Causality (Contd.)PDF unavailable
4Lecture 04: Correlation and Causality (Contd.)PDF unavailable
5Lecture 05: Probability TheoryPDF unavailable
6Lecture 06: Probability Theory (Contd.)PDF unavailable
7Lecture 07: Probability Theory (Contd.)PDF unavailable
8Lecture 08: Probability Theory (Contd.)PDF unavailable
9Lecture 09: Posterior ProbabilityPDF unavailable
10Lecture 10: Bayesian TheoremPDF unavailable
11Lecture 11: Bayesian Theorem (Contd.): Repeated TrialPDF unavailable
12Lecture 12: Bayesian Theorem (Contd.): Example of Diamond IdentificationPDF unavailable
13Lecture 13: Probability DistributionPDF unavailable
14Lecture 14: Double Structure of VariablePDF unavailable
15Lecture 15: Probability Distribution (Discrete/Continuous Variable) Random VariablePDF unavailable
16Lecture 16: Probability Mass Function (PMF) Probability Density Function (PDF)"PDF unavailable
17Lecture 17: Expectation, Variance, CovariancePDF unavailable
18Lecture 18: Expectation, Variance, Covariance (Contd.)PDF unavailable
19Lecture 19: Covariance RulePDF unavailable
20Lecture 20: Bernoulli DistributionPDF unavailable
21Lecture 21: Bernoulli Distribution (Contd.)PDF unavailable
22Lecture 22: Normal Approximation of Bernoulli DistributionPDF unavailable
23Lecture 23: SamplingPDF unavailable
24Lecture 24: Sampling (Contd.)PDF unavailable
25Lecture 25: Central Limit TheoremPDF unavailable
26Lecture 26: Law of Large Numbers LLNPDF unavailable
27Lecture 27: Properties of EstimatorPDF unavailable
28Lecture 28: Conflict Between Unbiasedness and Min VariancePDF unavailable
29Lecture 29: T - DistributionPDF unavailable
30Lecture 30: Normal DistributionPDF unavailable
31Lecture 31: Normal Distribution (Contd.)PDF unavailable
32Lecture 32: Hypothesis TestingPDF unavailable
33Lecture 33: Decision RulesPDF unavailable
34Lecture 34: Level of SignificancePDF unavailable
35Lecture 35: P ValuePDF unavailable
36Lecture 36: Power of a TestPDF unavailable
37Lecture 37: Confidence IntervalPDF unavailable
38Lecture 38: Confidence Interval ExamplePDF unavailable
39Lecture 39: Properties of Power of a TestPDF unavailable
40Lecture 40: Introduction to Module IIPDF unavailable
41Lecture 41: Error Term, Coefficient of Determination, Regression CoefficientPDF unavailable
42Lecture 42: Error Term, Coefficient of Determination, Regression Coefficient (Contd.)PDF unavailable
43Lecture 43: Error Term, Coefficient of Determination, Regression Coefficient (Contd.)PDF unavailable
44Lecture 44: Definition : Variable, Parameter and CoefficientPDF unavailable
45Lecture 45: Introduction to Regression: Recapitulating Correlation and Causal ThinkingPDF unavailable
46Lecture 46: Adjusted R-SquaredPDF unavailable
47Lecture 47: Degrees of FreedomPDF unavailable
48Lecture 48: Multiple RegressionPDF unavailable
49Lecture 49: Multiple Regression (Contd.)PDF unavailable
50Lecture 50: Regression TablePDF unavailable
51Lecture 51: Regression Table (Contd.)PDF unavailable
52Lecture 52: MulticollinearityPDF unavailable
53Lecture 53: Multicollinearity (Contd.)PDF unavailable
54Lecture 54: Multicollinearity (Contd.)PDF unavailable
55Lecture 55: Multicollinearity (Contd.)PDF unavailable
56Lecture 56: Multicollinearity (Contd.)PDF unavailable
57Lecture 57: Dummy VariablePDF unavailable
58Lecture 58: Dummy variable (Contd.)PDF unavailable
59Lecture 59: Dummy variable (Contd.)PDF unavailable
60Lecture 60: Dummy variable (Contd.)PDF unavailable
61Lecture 61: Dummy variable (Contd.)PDF unavailable
62Lecture 62: Dummy variable (Contd.)PDF unavailable
63Lecture 63: Dummy variable (Contd.)PDF unavailable
64Lecture 64: HeteroscedasticityPDF unavailable
65Lecture 65: Heteroscedasticity (Contd.)PDF unavailable
66Lecture 66 : Heteroscedasticity (Contd.)PDF unavailable
67Lecture 67 : Heteroscedasticity (Contd.)PDF unavailable
68Lecture 68 : Heteroscedasticity (Contd.)PDF unavailable
69Lecture 69 : Heteroscedasticity (Contd.)PDF unavailable


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