Advanced Sample Surveys

Paper Code: 
24STT423(B)
Credits: 
5
Contact Hours: 
75.00
Max. Marks: 
100.00
Objective: 

This is an advanced course in Sampling Techniques that aims at describing some advanced level topics for students who wish to pursue research in Sampling Techniques. This course prepares students for undertaking research in this area. This also helps prepare students for applications of this important subject to the Statistical System in the country.

 

Course Outcomes: 

Course

Course Outcomes

Learning and teaching strategies

Assessment Strategies

Course Code

Course Title

24STT423(B)

Advanced Sample Surveys

(Theory)

CO 136: Evaluate estimation methods with varying probabilities and analyze the Narain-Horvitz-Thompson estimator incorporating inclusion probabilities.

CO 137: Analyze the estimation of variance for the Horvitz-Thompson estimator, Midzuno Sampling scheme and Rao-Hartley-Cochran sampling scheme.

CO 138: Explore Brewer’s sampling design and its multivariate extensions for ratio and regression estimates, evaluating their optimal properties.

CO 139: Examine subsampling techniques using varying probabilities with and without replacement along with Naraine Sukhatme sampling schemes I and II.

CO 140: Investigate double sampling in regression estimation, successive sampling for multiple occasions, and introduce super population concepts and models to understand population dynamics and sampling strategies.

CO 141: Contribute effectively in course-specific interaction.

Approach in teaching: 

Interactive Lectures, 

Group Discussion, 

Classroom Assignment,

Problem Solving Sessions.

 

Learning activities for the students:

Assignments,

Seminar,

Presentation,

Subject based  Activities.

Classroom Quiz,

Assignments,

Class Test,

Individual Presentation.

 

15.00
Unit I: 
Estimation with Varying Probabilities and Without Replacement

Varying probabilities and without replacement. Des Raj ordered estimates, Murthy’s unordered estimates (general cases), estimation of linear classes of estimates, Narain-Horvitz-Thompson’s estimator and variance. Inclusion probabilities(n=2).

 

15.00
Unit II: 
Variance Estimation and Sampling Schemes

Estimation of variance of Horvitz-Thompson estimator, Horvitz-Thompson, Yates-Grundy, Sen-Midzuno’s results, Midzuno Sampling scheme. Rao-Hartley-Cochran sampling scheme.

 

15.00
Unit III: 
Advanced Sampling Designs and Estimation Methods

Brewer’s sampling design, multivariate extensions of ratio and regression estimates. Optimal properties of ratio and regression method of estimation.

 

15.00
Unit IV: 
Subsampling with Varying Probabilities

Sub sampling using varying probabilities with and without replacement: unbiased estimator, its variance and estimates of the variance, Durbin’s result. Naraine Sukhatme sampling schemes I and II.

 

15.00
Unit V: 
Double Sampling and Superpopulation Concepts

Double sampling in regression estimation, successive sampling for h ≥ 2 ocassions. Super population concepts and super population models (introduction).

 

Essential Readings: 
  • Cocharan,W.G.(1997): Sampling Techniques III ed, John Wiley Pub. New Yark.
  • Des Raj and Chandok (1999): Sampling Theory , Norsa Pub. New Delhi.
  • Murthy , M.N. (1967) : Sampling Theory and Methods, Statistical Pub.Society, Kolkata .
  • Chaudhary, A and. Mukherjee R (1988): Randomised Response: Theory & Techniques, Marcel Dekker Inc New Yark.

 

SUGGESTED READINGS:

  • Shukhatme, P.V.et al(1984): Sampling Theory of Surveys in the Applications, Iawa State press & Ind.Soc. of Agri. Stat.
  • Mukhopadhya, P.(1996): Inferencial Problems in Survey Sampling, New Age Intenational.
  • Singh, D. & Choudhary,F.S.(2002): Theory and Analysis of Sample Surveys and its  Applications, New Age international Publication.

 

e-RESOURCES:

 

JOURNALS:

  • Sankhya The Indian Journal of Statistics, Indian Statistical Institute
  • Aligarh Journal of Statistics, Department of Statistics and Operations Research, Aligarh Muslim University
  • Afrika Statistika, Saint-Louis Senega University
  • International Journal of Statistics and Reliability Engineering, Indian Association for Reliability and Statistic
  • Journal of the Indian Society for Probability and Statistics, Indian Society for Probability and Statistics
  • Journal of the Indian Statistical Association, Indian Statistical Association
  • Statistica, Department of Statistical Sciences Paolo Fortunato, University of Bologna
  • Statistics and Applications, Society of Statistics, Computer and Applications
  • Stochastic Modeling and Applications, MUK Publications and Distributions

 

Academic Year: 
2024-2025
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