Modules / Lectures

Module Name | Download |
---|---|

noc21_ma36_assignment_Week_1 | noc21_ma36_assignment_Week_1 |

noc21_ma36_assignment_Week_10 | noc21_ma36_assignment_Week_10 |

noc21_ma36_assignment_Week_11 | noc21_ma36_assignment_Week_11 |

noc21_ma36_assignment_Week_12 | noc21_ma36_assignment_Week_12 |

noc21_ma36_assignment_Week_2 | noc21_ma36_assignment_Week_2 |

noc21_ma36_assignment_Week_3 | noc21_ma36_assignment_Week_3 |

noc21_ma36_assignment_Week_4 | noc21_ma36_assignment_Week_4 |

noc21_ma36_assignment_Week_5 | noc21_ma36_assignment_Week_5 |

noc21_ma36_assignment_Week_6 | noc21_ma36_assignment_Week_6 |

noc21_ma36_assignment_Week_7 | noc21_ma36_assignment_Week_7 |

noc21_ma36_assignment_Week_8 | noc21_ma36_assignment_Week_8 |

noc21_ma36_assignment_Week_9 | noc21_ma36_assignment_Week_9 |

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

1 | Lecture 01: What is Data Science? | Download |

2 | Lecture 02: Installation and Working with R | Download |

3 | Lecture 03: Calculations with R as a Calculator | Download |

4 | Lecture 04: Calculations with Data Vectors | Download |

5 | Lecture 05: Built-in Commands and Missing Data Handling | Download |

6 | Lecture 06: Operations with Matrices | Download |

7 | Lecture 07: Data Handling | Download |

8 | Lecture 08: Graphics and Plots | Download |

9 | Lecture 09: Sampling, Sampling Unit, Population and Sample | Download |

10 | Lecture 10: Terminologies and Concepts | Download |

11 | Lecture 11: Ensuring Representativeness and Type of Surveys | Download |

12 | Lecture 12: Conducting Surveys and Ensuring Representativeness | Download |

13 | Lecture 13: SRSWOR, SRSWR, and Selection of Unit- 1 | Download |

14 | Lecture 14: SRSWOR, SRSWR, and Selection of Unit- 2 | Download |

15 | Lecture 15: Probabilities of Selection of Samples | Download |

16 | Lecture 16: SRSWOR and SRSWR with R with "sample" Package | Download |

17 | Lecture 17: Examples of SRS with R using "sample" Package | Download |

18 | Lecture 18: Simple Random Sampling :: SRS with R using “sampling” and “sample” Packages | Download |

19 | Lecture 19: Simple Random Sampling :: Estimation of Population Mean | Download |

20 | Lecture 20: Simple Random Sampling :: Estimation of Population Variance | Download |

21 | Lecture 21: Simple Random Sampling :: Estimation of Population Variance | Download |

22 | Lecture 22: SRS :: Confidence Interval Estimation of Population Mean | Download |

23 | Lecture 23: SRS :: Estimation of Mean, Variance and Confidence Interval in SRSWOR using R | Download |

24 | Lecture 24: SRS :: Estimation of Mean, Variance and Confidence Interval in SRSWR using R | Download |

25 | Lecture 25: Sampling for Proportions and Percentages :: Basic Concepts | Download |

26 | Lecture 26: Sampling for Proportions and Percentages :: Mean and Variance of Sample Proportion | Download |

27 | Lecture 27: Sampling for Proportions and Percentages :: Sampling for Proportions with R | Download |

28 | Lecture 28: Stratified Random Sampling :: Drawing the Sample and Sampling Procedure | Download |

29 | Lecture 29: Stratified Random Sampling :: Estimation of Population Mean, Population Variance and Confidence Interval | Download |

30 | Lecture 30: Stratified Random Sampling :: Sample Allocation and Variances Under Allocation | Download |

31 | Lecture 31: Stratified Random Sampling :: Drawing of Sample Using sampling and strata Packages in R | Download |

32 | Lecture 32: Stratified Random Sampling :: Drawing of Sample Using survey Package in R | Download |

33 | Lecture 33: Bootstrap Methodology :: What is Bootstrap and Methodology | Download |

34 | Lecture 34: Bootstrap Methodology :: EDF, Bootstrap Bias and Bootstrap Standard Errors | Download |

35 | Lecture 35: Bootstrap Methodology :: Bootstrap Analysis Using boot Package in R | Download |

36 | Lecture 36: Bootstrap Methodology :: Bootstrap Confidence Interval | Download |

37 | Lecture 37: Bootstrap Methodology :: Bootstrap Confidence Interval Using boot and bootstrap Packages in R | Download |

38 | Lecture 38: Bootstrap Methodology :: Example of Bootstrap Analysis Using boot Package | Download |

39 | Lecture 39: Introduction to Linear Models and Regression :: Introduction and Basic Concepts | Download |

40 | Lecture 40: Simple Linear Regression Analysis :: Basic Concepts and Least Squares Estimation | Download |

41 | Lecture 41: Simple Linear Regression Analysis :: Fitting Linear Model With R Software | Download |

42 | Lecture 42: Simple Linear Regression Analysis :: Properties of Least Squares Estimators | Download |

43 | Lecture 43: Simple Linear Regression Analysis :: Maximum Likelihood and Confidence Interval Estimation | Download |

44 | Lecture 44: Simple Linear Regression Analysis :: Test of Hypothesis and Confidence Interval Estimation With R | Download |

45 | Lecture 45: Multiple Linear Regression Analysis :: Basic Concepts | Download |

46 | Lecture 46: Multiple Linear Regression Analysis :: OLSE, Fitted Model and Residuals | Download |

47 | Lecture 47: Multiple Linear Regression Analysis :: Model Fitting With R Software | Download |

48 | Lecture 48: Multiple Linear Regression Analysis :: Properties of OLSE and Maximum Likelihood Estimation | Download |

49 | Lecture 49: Multiple Linear Regression Analysis :: Test of Hypothesis and Confidence Interval Estimation on Individual Regression Coefficients | Download |

50 | Lecture 50: Analysis of Variance and Implementation in R Software | Download |

51 | Lecture 51: Goodness of Fit and Implementation in R Software | Download |

52 | Lecture 52: Variable Selection using LASSO Regression :: Introduction and Basic Concepts | Download |

53 | Lecture 53: Variable Selection using LASSO Regression :: LASSO with R | Download |

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

1 | Lecture 01: What is Data Science? | Download Verified |

2 | Lecture 02: Installation and Working with R | Download Verified |

3 | Lecture 03: Calculations with R as a Calculator | Download Verified |

4 | Lecture 04: Calculations with Data Vectors | Download Verified |

5 | Lecture 05: Built-in Commands and Missing Data Handling | Download Verified |

6 | Lecture 06: Operations with Matrices | Download Verified |

7 | Lecture 07: Data Handling | Download Verified |

8 | Lecture 08: Graphics and Plots | Download Verified |

9 | Lecture 09: Sampling, Sampling Unit, Population and Sample | Download Verified |

10 | Lecture 10: Terminologies and Concepts | Download Verified |

11 | Lecture 11: Ensuring Representativeness and Type of Surveys | Download Verified |

12 | Lecture 12: Conducting Surveys and Ensuring Representativeness | Download Verified |

13 | Lecture 13: SRSWOR, SRSWR, and Selection of Unit- 1 | Download Verified |

14 | Lecture 14: SRSWOR, SRSWR, and Selection of Unit- 2 | Download Verified |

15 | Lecture 15: Probabilities of Selection of Samples | Download Verified |

16 | Lecture 16: SRSWOR and SRSWR with R with "sample" Package | Download Verified |

17 | Lecture 17: Examples of SRS with R using "sample" Package | Download Verified |

18 | Lecture 18: Simple Random Sampling :: SRS with R using “sampling” and “sample” Packages | Download Verified |

19 | Lecture 19: Simple Random Sampling :: Estimation of Population Mean | Download Verified |

20 | Lecture 20: Simple Random Sampling :: Estimation of Population Variance | Download Verified |

21 | Lecture 21: Simple Random Sampling :: Estimation of Population Variance | Download Verified |

22 | Lecture 22: SRS :: Confidence Interval Estimation of Population Mean | Download Verified |

23 | Lecture 23: SRS :: Estimation of Mean, Variance and Confidence Interval in SRSWOR using R | Download Verified |

24 | Lecture 24: SRS :: Estimation of Mean, Variance and Confidence Interval in SRSWR using R | Download Verified |

25 | Lecture 25: Sampling for Proportions and Percentages :: Basic Concepts | Download Verified |

26 | Lecture 26: Sampling for Proportions and Percentages :: Mean and Variance of Sample Proportion | Download Verified |

27 | Lecture 27: Sampling for Proportions and Percentages :: Sampling for Proportions with R | Download Verified |

28 | Lecture 28: Stratified Random Sampling :: Drawing the Sample and Sampling Procedure | Download Verified |

29 | Lecture 29: Stratified Random Sampling :: Estimation of Population Mean, Population Variance and Confidence Interval | Download Verified |

30 | Lecture 30: Stratified Random Sampling :: Sample Allocation and Variances Under Allocation | Download Verified |

31 | Lecture 31: Stratified Random Sampling :: Drawing of Sample Using sampling and strata Packages in R | Download Verified |

32 | Lecture 32: Stratified Random Sampling :: Drawing of Sample Using survey Package in R | Download Verified |

33 | Lecture 33: Bootstrap Methodology :: What is Bootstrap and Methodology | Download Verified |

34 | Lecture 34: Bootstrap Methodology :: EDF, Bootstrap Bias and Bootstrap Standard Errors | Download Verified |

35 | Lecture 35: Bootstrap Methodology :: Bootstrap Analysis Using boot Package in R | Download Verified |

36 | Lecture 36: Bootstrap Methodology :: Bootstrap Confidence Interval | Download Verified |

37 | Lecture 37: Bootstrap Methodology :: Bootstrap Confidence Interval Using boot and bootstrap Packages in R | Download Verified |

38 | Lecture 38: Bootstrap Methodology :: Example of Bootstrap Analysis Using boot Package | Download Verified |

39 | Lecture 39: Introduction to Linear Models and Regression :: Introduction and Basic Concepts | Download Verified |

40 | Lecture 40: Simple Linear Regression Analysis :: Basic Concepts and Least Squares Estimation | Download Verified |

41 | Lecture 41: Simple Linear Regression Analysis :: Fitting Linear Model With R Software | Download Verified |

42 | Lecture 42: Simple Linear Regression Analysis :: Properties of Least Squares Estimators | PDF unavailable |

43 | Lecture 43: Simple Linear Regression Analysis :: Maximum Likelihood and Confidence Interval Estimation | PDF unavailable |

44 | Lecture 44: Simple Linear Regression Analysis :: Test of Hypothesis and Confidence Interval Estimation With R | PDF unavailable |

45 | Lecture 45: Multiple Linear Regression Analysis :: Basic Concepts | PDF unavailable |

46 | Lecture 46: Multiple Linear Regression Analysis :: OLSE, Fitted Model and Residuals | PDF unavailable |

47 | Lecture 47: Multiple Linear Regression Analysis :: Model Fitting With R Software | PDF unavailable |

48 | Lecture 48: Multiple Linear Regression Analysis :: Properties of OLSE and Maximum Likelihood Estimation | PDF unavailable |

49 | Lecture 49: Multiple Linear Regression Analysis :: Test of Hypothesis and Confidence Interval Estimation on Individual Regression Coefficients | PDF unavailable |

50 | Lecture 50: Analysis of Variance and Implementation in R Software | PDF unavailable |

51 | Lecture 51: Goodness of Fit and Implementation in R Software | PDF unavailable |

52 | Lecture 52: Variable Selection using LASSO Regression :: Introduction and Basic Concepts | PDF unavailable |

53 | Lecture 53: Variable Selection using LASSO Regression :: LASSO with R | PDF unavailable |

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

1 | English | Download |

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 |