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Sampling Techniques
The students would be exposed to elementary, systematic, stratified and two stage sampling techniques. It would help them in understanding the concepts involved in planning and designing their surveys, presentation of survey data analysis of survey data and presentation of results.
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Learning outcomes (at course level |
Learning and teaching strategies |
Assessment Strategies
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Paper Code |
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STT223 |
Sampling Techniques (Theory) |
The students will be able to –
CO37: Determine the sample is a simple random sample, a voluntary response sample, a convenience sample, or has other forms of sampling bias. CO38: Analyse the data from multi-stage surveys. CO39: Able to recognize typical forms of biases such as potential under coverage, non-response and response bias. CO40: Identify the type of data and also able to take decision of appropriate sampling scheme.
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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 |
Simple random sampling with and without replacement: Definition, properties, estimation of population mean, its variance and estimates of variance, optimum properties of sample mean, estimation of sample size, estimation of properties, Inverse sampling.
Stratified Sampling: estimation of population, mean under proportional, optimum and Neyman allocation, comparison and estimation of gain in precision, Post stratification. Systematic sampling: estimation of mean, its variance and estimation of variance. Comparison with stratified sampling. Cluster sampling and two stage sampling with unequal number of second stage unit.
Use of Auxiliary Information: Ratio, difference, regression and product methods of estimation and properties. Unbiased ratio type estimates: Hartley& Ross, Quenoullie’s Techniques.
Double sampling and its uses in ratio estimation, Stratified sampling. Population proportion to size with replacement and without replacement (PPSWR or PPSWOR) sampling, cumulative total and Lahiri’s method. Ratio estimator under varying probabilities, Midzuno scheme of sampling.
Non Sampling errors: observational error, mathematical model, the sample mean, its variance and estimation of the variance. Non-Response error: Hanson and Horvitz, Politz & Simmon Warness technique.
- Cocharan, W.G.(1997): Sampling Techniques III ed, John Wiley Pub. New York.
- Murthy, MN. (1977) Sampling Theory and Methods, 2nd Ed. Statistical Publ. Soc., Calcutta.
- Singh D., Singh, P. & Kumar P. (1982): Handbook on Sampling Methods, IASRI Publ.
- Sukhatme, P.V., Sukhatme, B.V., Sukhatme, S. & Asok, C. (1984): Sampling Theory of Surveys with Applications, Iowa State University Press and Indian Society of Agricultural Statistics, New Delhi.
- Chaudhuri, A. and Mukerjee, R. (1988):Randomized Responses .Theory and Techniques, New York : Marcel Dekker Inc.
- Des Raj and Chandok (1999): Sampling Theory, Norsa Pub. New Delhi.
- Sampath, S. (2000): Sampling theory and Methods, Narosa Publishing House.
- Singh, D. and Chaudhary ,F.S. (1986):Theory and Analysis of Sample Survey Designs, New Age International Publishers.
- Mukhopadhya, P.(1996): Inferencial Problems in Survey Sampling, New Age International.
- Singh, R. and Mangat, M.S. (1996): Elements of Sample Survey, Springer
- Singh, Sarjinder (2003): Advanced Sampling Theory with Applications: How Michael 'selected' Amy, Volume 2, Kluwer Academic Publishers
