Shalabh
shalab@iitk.ac.in
shalabh1@yahoo.com
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur, Kanpur - 208016 (India)

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Introduction to Sampling Theory

Swayam Prabha Course

The forty hours course is for the students in Bachelor's and Master's programmes and covers the topics of sampling theory.

Suggested books:

1.      Sampling Techniques : W.G. Cochran, Wiley (Low price edition available)

2.      Theory and Methods of Survey Sampling : Parimal Mukhopadhyay, Prentice Hall of India

3.      Theory of Sample surveys with applications : P.V. Sukhatme, B.V Sukhatme, S. Sukhatme and C. Asok, IASRI, Delhi

4.      Sampling Methodologies and Applications : P.S.R.S. Rao, Chapman and Hall/ CRC

5.      Elements of sampling theory and methods : Z. Govindrajalu, Prentice Hall

7.   Sampling Methods- Exercises and Solutions : Pascal Ardilly and Yves Tille'

 

Language of the course: English

 

Duration of the course: 40 Hours

 

Swayam Prabha DTH Channel 16 Youtube link: The telecasted lectures are available at  YouTube (Click here)

 

Slides and Videos used in the lectures: 

 

 

Lecture videos download links

Lecture slides download links

Brief Description

Lecture Title

Lecture No.

Click here Lecture 1

Click here Lecture 1

Basic definitions

Basic Definitions and Fundamentals

1

Click here Lecture 2

Click here Lecture 2

Ensuring representativeness, Advantages of Sampling Over Complete Enumeration, Type of Surveys

Basic Definitions and Fundamentals

2

Click here Lecture 3

Click here Lecture 3

Principal Steps in Conducting a Survey, Methods of Data Collection

Basic Definitions and Fundamentals

3

Click here Lecture 4

Click here Lecture 4

SRSWOR, SRSWR and basic concepts

Simple Random Sampling

4

Click here Lecture 5

Click here Lecture 5

Probability of Selection of a Sample and a Unit

Simple Random Sampling

5

Click here Lecture 6

Click here Lecture 6

Estimation of population mean and variance

Simple Random Sampling

6

Click here Lecture 7

Click here Lecture 7

Estimation of variance and Confidence interval estimation  

Simple Random Sampling

7

Click here Lecture 8

Click here Lecture 8

Confidence interval estimation  and Sample size determination

Simple Random Sampling

8

Click here Lecture 9

Click here Lecture 9

SRSWOR, SRSWR and basic concepts

Simple Random Sampling for Proportions and Percentages

9

Click here Lecture 10

Click here Lecture 10

Estimation of population mean and related topics

Simple Random Sampling for Proportions and Percentages

10

Click here Lecture 11

Click here Lecture 11

Estimation of population proportion, its  variance, confidence interval estimation and inverse sampling

Simple Random Sampling for Proportions and Percentages

11

Click here Lecture 12

Click here Lecture 12

Basic concepts and sampling procedure

Stratified Sampling

12

Click here Lecture 13

Click here Lecture 13

Advantages of  Stratified Sampling and Estimation of Population Mean and Variance

Stratified Sampling

13

Click here Lecture 14

Click here Lecture 14

Sample allocation and the Variances of stratum mean under allocations

Stratified Sampling

14

Click here Lecture 15

Click here Lecture 15

Basic concepts and Bias of Ratio Estimator

Ratio Method of Estimation

15

Click here Lecture 16

Click here Lecture 16

Mean Squared Error of Ratio Estimator

Ratio Method of Estimation

16

Click here Lecture 17

Click here Lecture 17

Efficiency of Ratio Estimator, Upper Limit of Ratio Estimator and estimate of MSE

Ratio Method of Estimation

17

Click here Lecture 18

Click here Lecture 18

Ratio Estimator in Stratified Sampling

Ratio Method of Estimation

18

Click here Lecture 19

Click here Lecture 19

Unbiased Ratio-type Estimators and Product method of estimation

Unbiased Ratio Type Estimators and Product Method of Estimation

19

Click here Lecture 20

Click here Lecture 20

Post Stratification and MSE of Multivariate Ratio Estimator

Post Stratification and Multivariate Ratio Estimator

20

Click here Lecture 21

Click here Lecture 21

Basics and fundamentals, Regression estimates with pre-assigned regression coefficient, estimate of variance

Regression Method of Estimation

21

Click here Lecture 22

Click here Lecture 22

Bias and Mean Squared Error of the Regression Estimates, Comparison with Sample Random Sampling

Regression Method of Estimation

22

Click here Lecture 23

Click here Lecture 23

Regression method in stratified sampling

Regression Method of Estimation

23

Click here Lecture 24

Click here Lecture 24

Basic definitions and concepts

Varying Probability Sampling

24

Click here Lecture 25

Click here Lecture 25

Probability proportional to size and sample drawing methods

Varying Probability Sampling

25

Click here Lecture 26

Click here Lecture 26

PPS in sampling with replacement and related topics

Varying Probability Sampling

26

Click here Lecture 27

Click here Lecture 27

PPS in sampling without  replacement and ordered estimators

Varying Probability Sampling

27

Click here Lecture 28

Click here Lecture 28

Unordered estimators, Murthy's  Estimator and Horwitz Thompson Estimator and related topics

Varying Probability Sampling

28

Click here Lecture 29

Click here Lecture 29

Horwitz Thompson Estimator and Midzuno System of Sampling

Varying Probability Sampling

29

Click here Lecture 30

Click here Lecture 30

Double sampling in ratio method of estimation

Double Sampling

30

Click here Lecture 31

Click here Lecture 31

Double sampling in regression method of estimation

Double Sampling

31

Click here Lecture 32

Click here Lecture 32

Basic concepts, Estimation of population mean and Variance with equal size clusters

Cluster Sampling

32

Click here Lecture 33

Click here Lecture 33

Comparison of cluster sampling with simple random sampling

Cluster Sampling

33

Click here Lecture 34

Click here Lecture 34

Estimation of a Proportion in case of Equal Cluster, estimation of population mean with unequal size clusters

Cluster Sampling

34

Click here Lecture 35

Click here Lecture 35

Basic concepts and estimation of population mean with unequal size clusters

Cluster Sampling

35

Click here Lecture 36

Click here Lecture 36

Basic concepts and estimation of population mean with equal first stage units

Two Stage Sampling

36

Click here Lecture 37

Click here Lecture 37

Basic concepts and estimation of population mean with unequal first stage units

Two Stage Sampling

37

Click here Lecture 38

Click here Lecture 38

Basic fundamentals, definitions and estimation of population mean

Systematic Sampling

38

Click here Lecture 39

Click here Lecture 39

Various results of systematic sampling and its relation to other sampling schemes

Systematic Sampling

39

Click here Lecture 40

Click here Lecture 40

Basic fundamentals and definitions

Non Sampling Errors

40

 

Lecture notes for your help (If you find any typo, please let me know)

Lecture Notes 1 : Introduction

Lecture Notes 2 : Simple Random Sampling

Lecture Notes 3 : Sampling For Proportions and Percentages

Lecture Notes 4 : Stratified Sampling

Lecture Notes 5 : Ratio and Product Methods of Estimation

Lecture Notes 6  : Regression Method of Estimation

Lecture Notes 7  : Varying Probability Sampling

Lecture Notes 8  : Double Sampling (Two Phase Sampling)

Lecture Notes 9  : Cluster Sampling

Lecture Notes 10  : Two Stage Sampling (Subsampling)

Lecture Notes 11  :  Systematic Sampling

Lecture Notes 12  : Sampling on Successive Occasions

Lecture Notes 13  : Non Sampling Errors