| 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 |