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.
Students will able to
Course |
Learning outcomes (at course level |
Learning and teaching strategies |
Assessment Strategies
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Paper Code |
Paper Title |
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STT-223 |
Sampling Techniques |
CO 38: Select the appropriate sampling techniques for conducting the sample surveys.
CO 39: Analyse the data from multi-stage surveys.
CO 40: Recognize typical forms of biases such as potential under coverage, non-response and response bias.
CO 41: Conduct sample surveys within the context of socially acceptable professional and ethical practices. |
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.