Modules / Lectures

Module Name | Download |
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noc21_hs39_assignment_Week_1 | noc21_hs39_assignment_Week_1 |

noc21_hs39_assignment_Week_10 | noc21_hs39_assignment_Week_10 |

noc21_hs39_assignment_Week_11 | noc21_hs39_assignment_Week_11 |

noc21_hs39_assignment_Week_12 | noc21_hs39_assignment_Week_12 |

noc21_hs39_assignment_Week_2 | noc21_hs39_assignment_Week_2 |

noc21_hs39_assignment_Week_3 | noc21_hs39_assignment_Week_3 |

noc21_hs39_assignment_Week_4 | noc21_hs39_assignment_Week_4 |

noc21_hs39_assignment_Week_5 | noc21_hs39_assignment_Week_5 |

noc21_hs39_assignment_Week_6 | noc21_hs39_assignment_Week_6 |

noc21_hs39_assignment_Week_7 | noc21_hs39_assignment_Week_7 |

noc21_hs39_assignment_Week_8 | noc21_hs39_assignment_Week_8 |

noc21_hs39_assignment_Week_9 | noc21_hs39_assignment_Week_9 |

Sl.No | Chapter Name | MP4 Download |
---|---|---|

1 | Lecture 1: Introduction to Statistics | Download |

2 | Lecture 2: Introduction to Econometrics | Download |

3 | Lecture 3: Organization & Presentation of Data | Download |

4 | Lecture 4: Summarizing Data through Descriptive Statistics | Download |

5 | Lecture 5: Discrete Random Variable & Probability Distribution | Download |

6 | Lecture 6: Continuous Random Variables & Probability Distribution | Download |

7 | Lecture 7: Normal Distribution | Download |

8 | Lecture 8: Introduction to Statistical Inference | Download |

9 | Lecture 9: Estimation (Part I) | Download |

10 | Lecture 10: Estimation (Part II) | Download |

11 | Lecture 11: Hypothesis Testing (Part I) | Download |

12 | Lecture 12: Hypothesis Testing (Part II) | Download |

13 | Lecture 13: Hypothesis Testing (Part III) | Download |

14 | Lecture 14: Hypothesis Testing (Part IV) | Download |

15 | Lecture 15: Relationship between Qualitative Variables | Download |

16 | Lecture 16: Relationship Between Quantitative Variables | Download |

17 | Lecture 17: Analysis of Variance | Download |

18 | Lecture 18: One Way ANOVA | Download |

19 | Lecture 19: Two Way ANOVA | Download |

20 | Lecture 20: Analysis of Covariance | Download |

21 | Lecture 21: Index Number (Part I) | Download |

22 | Lecture 22: Index Numbers (Part II) | Download |

23 | Lecture 23: Classical Time Series Analysis (Part I) | Download |

24 | Lecture 24: Classical Time Series Analysis (Part II) | Download |

25 | Lecture 25: Classical Linear Regression Model (Part-I) | Download |

26 | Lecture 26: Classical Linear Regression Model (Part-II) | Download |

27 | Lecture 28: Hypothesis Testing with CNLRM | Download |

28 | Lecture 29: More on Hypothesis Testing and Model Specification | Download |

29 | Lecture 30: Violations of CLRM Assumptions (Heteroskedasticity) | Download |

30 | Lecture 31: Violations of CLRM Assumptions (Autocorrelation and Multicollinearity) | Download |

31 | Lecture 32: Time Series Regression with Stationary Data | Download |

32 | Lecture 33: Time Series Regression with Non-Stationary Data | Download |

33 | Lecture 34: Regression with Dummy Explanatory Variable | Download |

34 | Lecture 35: Dummy Dependent Variable Models (Part-I) | Download |

35 | Lecture 36: Dummy Dependent Variable Models (Part-II) | Download |

36 | Lecture 37: Simultaneous Equations Model | Download |

37 | Lecture 38: Panel Data Regression | Download |

38 | Lecture 39: Program Evaluation | Download |

39 | Lecture 40: Data Analysis and Regression with R | Download |

40 | Lecture 41: Regression Involving Dummy Variables in R | Download |

41 | Lecture 42: Time Series Analysis in R | Download |

Sl.No | Chapter Name | English |
---|---|---|

1 | Lecture 1: Introduction to Statistics | Download To be verified |

2 | Lecture 2: Introduction to Econometrics | Download To be verified |

3 | Lecture 3: Organization & Presentation of Data | Download To be verified |

4 | Lecture 4: Summarizing Data through Descriptive Statistics | Download To be verified |

5 | Lecture 5: Discrete Random Variable & Probability Distribution | Download To be verified |

6 | Lecture 6: Continuous Random Variables & Probability Distribution | Download To be verified |

7 | Lecture 7: Normal Distribution | Download To be verified |

8 | Lecture 8: Introduction to Statistical Inference | Download To be verified |

9 | Lecture 9: Estimation (Part I) | Download To be verified |

10 | Lecture 10: Estimation (Part II) | Download To be verified |

11 | Lecture 11: Hypothesis Testing (Part I) | Download To be verified |

12 | Lecture 12: Hypothesis Testing (Part II) | Download To be verified |

13 | Lecture 13: Hypothesis Testing (Part III) | Download To be verified |

14 | Lecture 14: Hypothesis Testing (Part IV) | Download To be verified |

15 | Lecture 15: Relationship between Qualitative Variables | Download To be verified |

16 | Lecture 16: Relationship Between Quantitative Variables | Download To be verified |

17 | Lecture 17: Analysis of Variance | Download To be verified |

18 | Lecture 18: One Way ANOVA | Download To be verified |

19 | Lecture 19: Two Way ANOVA | Download To be verified |

20 | Lecture 20: Analysis of Covariance | Download To be verified |

21 | Lecture 21: Index Number (Part I) | Download To be verified |

22 | Lecture 22: Index Numbers (Part II) | Download To be verified |

23 | Lecture 23: Classical Time Series Analysis (Part I) | Download To be verified |

24 | Lecture 24: Classical Time Series Analysis (Part II) | PDF unavailable |

25 | Lecture 25: Classical Linear Regression Model (Part-I) | PDF unavailable |

26 | Lecture 26: Classical Linear Regression Model (Part-II) | PDF unavailable |

27 | Lecture 28: Hypothesis Testing with CNLRM | PDF unavailable |

28 | Lecture 29: More on Hypothesis Testing and Model Specification | PDF unavailable |

29 | Lecture 30: Violations of CLRM Assumptions (Heteroskedasticity) | PDF unavailable |

30 | Lecture 31: Violations of CLRM Assumptions (Autocorrelation and Multicollinearity) | PDF unavailable |

31 | Lecture 32: Time Series Regression with Stationary Data | PDF unavailable |

32 | Lecture 33: Time Series Regression with Non-Stationary Data | PDF unavailable |

33 | Lecture 34: Regression with Dummy Explanatory Variable | PDF unavailable |

34 | Lecture 35: Dummy Dependent Variable Models (Part-I) | PDF unavailable |

35 | Lecture 36: Dummy Dependent Variable Models (Part-II) | PDF unavailable |

36 | Lecture 37: Simultaneous Equations Model | PDF unavailable |

37 | Lecture 38: Panel Data Regression | PDF unavailable |

38 | Lecture 39: Program Evaluation | PDF unavailable |

39 | Lecture 40: Data Analysis and Regression with R | PDF unavailable |

40 | Lecture 41: Regression Involving Dummy Variables in R | PDF unavailable |

41 | Lecture 42: Time Series Analysis in R | PDF unavailable |

Sl.No | Language | Book link |
---|---|---|

1 | English | Not Available |

2 | Bengali | Not Available |

3 | Gujarati | Not Available |

4 | Hindi | Not Available |

5 | Kannada | Not Available |

6 | Malayalam | Not Available |

7 | Marathi | Not Available |

8 | Tamil | Not Available |

9 | Telugu | Not Available |