Shalabh
shalab@iitk.ac.in
shalabh1@yahoo.com
Department of Mathematics & Statistics
Indian
MTH 432M/432A : Introduction to Sampling Theory
Syllabus : Principles of sample surveys; Simple, stratified and unequal probability sampling with and without replacement; ratio, product and regression method of estimation, Varying Probability Scheme
Books: You can
choose any one of the following book for your reference. Books at serial
numbers 1 and 2 are easily available, so I will base my lectures on them. Other
books are available in the library.
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,
4.
Sampling Methodologies and Applications : P.S.R.S. Rao, Chapman and Hall/ CRC
5.
Sampling Theory and Methods : M.N. Murthy, Statistical
Publishing Society,
6. Elements of sampling theory and methods : Z. Govindrajalu, Prentice Hall
7. Sampling Methods- Exercises and Solutions : Pascal Ardilly and Yves Tille' (Download here through IITK Library link)
Course Policy: Earn your marks and grades. I will be the happiest instructor to award the best grades to all the students.
Grading Scheme: Quiz- 40%, Mid Sem.- 60%
Class Schedule: Class begins: 31 July 2023. Time table: Mon, Wed, Thu, Fri 8:00 Hrs - 8:50 Hrs.
Mid Semester Examination:
Contact hours: 24 X 7, by email, phone, what's app. (If possible and not so urgent, avoid calling between 12-7 AM.)
Announcements:
Assignments:
A link will be sent through email to all the students to upload their assignments.
Lecture notes for your help (If you find any typo, please let me know)
For the course MTH432 A, Lecture Notes 2, 3, 4, 5, 6 and 7 are required.
Other chapters are detailed for knowledge enhancement.
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
Lecture Notes
7
Lecture Notes
8
Lecture Notes
9
Lecture Notes
10
Lecture Notes
11
Lecture Notes
12
Lecture Notes
13
Lecture Videos:
The students are advised to access the video lectures via the MooKIT platform as the lectures may have pop up quiz. Missing the pop up quiz will be considered as absent or zero marks.
Slides and videos used in the lectures
(Lectures 1,2,3 are for those who have not studied Sampling Theory in UG Classes.
Lecture 20 and 23 were not possible to cover in the usual classroom teaching, so it is not a part of the syllabus in online mode but it is given for completeness)
The video lectures are also available at Swayam Prabha DTH Channel 16 Youtube link: The telecasted lectures are available at YouTube (Click here).
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 |
Basic concepts and sampling procedure |
Stratified Sampling |
11 |
Click here Lecture 12 |
Click here Lecture 12 |
Advantages of Stratified Sampling and Estimation of Population Mean and Variance |
Stratified Sampling |
12 |
Click here Lecture 13 |
Click here Lecture 13 |
Sample allocation and the Variances of stratum mean under allocations |
Stratified Sampling |
13 |
Click here Lecture 14 |
Click here Lecture 14 |
Allocation, variance under allocations, proportions |
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 |
Following videos are only for knowledge enhancement and not the part of syllabus.
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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 |