Coming soon
Advanced Sample Surveys
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.
Students will able to
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Learning and teaching strategies |
Assessment Strategies
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STT-423(B) |
Advanced Sample Surveys |
CO 119: Learn the principles underlying sampling as a means of making inferences about a population,
CO 120: Analyze the concepts of bias and sampling variability and strategies for reducing these biases.
CO 121: Learn about the re-sampling techniques for variance estimation independent and dependent random groups.
CO 122: Able to analyze data from multi-stage surveys,
CO 123: Have an appreciation of the practical issues arising in sampling studies. |
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 |
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).
Estimation of variance of Horvitz-Thompson estimator, Horvitz-Thompson, Yates-Grundy, Sen-Midzuno’s results, Midzuno Sampling scheme. Rao-Hartley-Cochran sampling scheme.
Brewer’s sampling design, multivariate extensions of ratio and regression estimates. Optimal properties of ratio and regression method of estimation.
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.
Double sampling in regression estimation, successive sampling for h ≥ 2 ocassions. Super population concepts and super population models (introduction).
● 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:
· https://epgp.inflibnet.ac.in/
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
