Modules / Lectures


Sl.No Chapter Name MP4 Download
1Lecture 1: Introduction to Statistics Download
2Lecture 2: Introduction to Econometrics Download
3Lecture 3: Organization & Presentation of Data Download
4Lecture 4: Summarizing Data through Descriptive Statistics Download
5Lecture 5: Discrete Random Variable & Probability Distribution Download
6Lecture 6: Continuous Random Variables & Probability Distribution Download
7Lecture 7: Normal Distribution Download
8Lecture 8: Introduction to Statistical Inference Download
9Lecture 9: Estimation (Part I) Download
10Lecture 10: Estimation (Part II) Download
11Lecture 11: Hypothesis Testing (Part I) Download
12Lecture 12: Hypothesis Testing (Part II) Download
13Lecture 13: Hypothesis Testing (Part III) Download
14Lecture 14: Hypothesis Testing (Part IV) Download
15Lecture 15: Relationship between Qualitative Variables Download
16Lecture 16: Relationship Between Quantitative Variables Download
17Lecture 17: Analysis of VarianceDownload
18Lecture 18: One Way ANOVADownload
19Lecture 19: Two Way ANOVA Download
20Lecture 20: Analysis of Covariance Download
21Lecture 21: Index Number (Part I) Download
22Lecture 22: Index Numbers (Part II) Download
23Lecture 23: Classical Time Series Analysis (Part I) Download
24Lecture 24: Classical Time Series Analysis (Part II) Download
25Lecture 25: Classical Linear Regression Model (Part-I) Download
26Lecture 26: Classical Linear Regression Model (Part-II) Download
27Lecture 28: Hypothesis Testing with CNLRM Download
28Lecture 29: More on Hypothesis Testing and Model Specification Download
29Lecture 30: Violations of CLRM Assumptions (Heteroskedasticity)Download
30Lecture 31: Violations of CLRM Assumptions (Autocorrelation and Multicollinearity) Download
31Lecture 32: Time Series Regression with Stationary Data Download
32Lecture 33: Time Series Regression with Non-Stationary Data Download
33Lecture 34: Regression with Dummy Explanatory Variable Download
34Lecture 35: Dummy Dependent Variable Models (Part-I)Download
35Lecture 36: Dummy Dependent Variable Models (Part-II)Download
36Lecture 37: Simultaneous Equations ModelDownload
37Lecture 38: Panel Data RegressionDownload
38Lecture 39: Program EvaluationDownload
39Lecture 40: Data Analysis and Regression with RDownload
40Lecture 41: Regression Involving Dummy Variables in RDownload
41Lecture 42: Time Series Analysis in RDownload

Sl.No Chapter Name English
1Lecture 1: Introduction to Statistics Download
To be verified
2Lecture 2: Introduction to Econometrics Download
To be verified
3Lecture 3: Organization & Presentation of Data Download
To be verified
4Lecture 4: Summarizing Data through Descriptive Statistics Download
To be verified
5Lecture 5: Discrete Random Variable & Probability Distribution Download
To be verified
6Lecture 6: Continuous Random Variables & Probability Distribution Download
To be verified
7Lecture 7: Normal Distribution Download
To be verified
8Lecture 8: Introduction to Statistical Inference Download
To be verified
9Lecture 9: Estimation (Part I) Download
To be verified
10Lecture 10: Estimation (Part II) Download
To be verified
11Lecture 11: Hypothesis Testing (Part I) Download
To be verified
12Lecture 12: Hypothesis Testing (Part II) Download
To be verified
13Lecture 13: Hypothesis Testing (Part III) Download
To be verified
14Lecture 14: Hypothesis Testing (Part IV) Download
To be verified
15Lecture 15: Relationship between Qualitative Variables Download
To be verified
16Lecture 16: Relationship Between Quantitative Variables Download
To be verified
17Lecture 17: Analysis of VarianceDownload
To be verified
18Lecture 18: One Way ANOVADownload
To be verified
19Lecture 19: Two Way ANOVA Download
To be verified
20Lecture 20: Analysis of Covariance Download
To be verified
21Lecture 21: Index Number (Part I) Download
To be verified
22Lecture 22: Index Numbers (Part II) Download
To be verified
23Lecture 23: Classical Time Series Analysis (Part I) Download
To be verified
24Lecture 24: Classical Time Series Analysis (Part II) PDF unavailable
25Lecture 25: Classical Linear Regression Model (Part-I) PDF unavailable
26Lecture 26: Classical Linear Regression Model (Part-II) PDF unavailable
27Lecture 28: Hypothesis Testing with CNLRM PDF unavailable
28Lecture 29: More on Hypothesis Testing and Model Specification PDF unavailable
29Lecture 30: Violations of CLRM Assumptions (Heteroskedasticity)PDF unavailable
30Lecture 31: Violations of CLRM Assumptions (Autocorrelation and Multicollinearity) PDF unavailable
31Lecture 32: Time Series Regression with Stationary Data PDF unavailable
32Lecture 33: Time Series Regression with Non-Stationary Data PDF unavailable
33Lecture 34: Regression with Dummy Explanatory Variable PDF unavailable
34Lecture 35: Dummy Dependent Variable Models (Part-I)PDF unavailable
35Lecture 36: Dummy Dependent Variable Models (Part-II)PDF unavailable
36Lecture 37: Simultaneous Equations ModelPDF unavailable
37Lecture 38: Panel Data RegressionPDF unavailable
38Lecture 39: Program EvaluationPDF unavailable
39Lecture 40: Data Analysis and Regression with RPDF unavailable
40Lecture 41: Regression Involving Dummy Variables in RPDF unavailable
41Lecture 42: Time Series Analysis in RPDF unavailable


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