MTH 432 : Introduction to Sampling Theory

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

HOME PAGE

MTH 432M: 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. Some books are availabe easily in market and 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, Delhi

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, Calcutta (Out of print)

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- 30%, Mid Sem.- 70%

Class Schedule: Class begins: 30 July 2024. Time table: Lectures: Tuesday, Wednesday, Thursday 8:00 Hrs - 9:00 Hrs. (L13) Tutorial: Friday (L13) 14:00-15:00

Mid Semester Examination:

Contact hours: 24 X 7, by email, phone, what's app. (If possible and not so urgent, avoid calling between 00:00-07:00 Hrs (12-7 AM))

Announcements:

Assignments: The assignments will be given at regular time intervals and will be available over the course page. All the assignments will be discussed in the class.

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

For the course MTH432M, 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 : 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

Lecture Videos:

Introductory Video (at Youtube)

Slides and videos used in the lectures

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.
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