Course Details
Subject {L-T-P / C} : MA5254 : Sampling Techiques { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Manas Ranjan Tripathy
Syllabus
Basic concept of sample surveys: Census and sample surveys, Advantages and disadvantages, Probability and non-probability sampling, Sampling unit, Sampling frame, Sampling and non-sampling error, Simple random sampling and Stratified random sampling: Procedure for selecting a random sample, Estimation of population parameters, Estimation of population Proportion, Confidence limits, Estimation of sample size, Principle of stratification, Advantages of stratification, Estimation of population mean and variance, Allocation of sample size in different strata, Relative precision of stratified random sampling over simple random sampling, Estimation of gain in precision due to stratification, Systematic random sampling: Sample selection procedure, Advantages and disadvantages, Estimation mean and its sampling variance, Comparison of simple random sampling with stratified random sampling in some specified populations, Cluster sampling: Equal cluster sampling, Estimator of mean and its variance, Relative efficiency of cluster sampling, Optimum cluster size, Cluster sampling for proportions.
Course Objectives
- To give some overall view of various sampling schemes which are useful in statistical analysis of real data.
- To understand the sampling and non-sampling error, simple random sampling and stratified random sampling: procedure for selecting a random sample,
- To learn the estimation of population parameters, estimation of population proportion, confidence limits, estimation of sample size, principle of stratification, advantages of stratification, estimation of population mean and variance,
- To compare simple random sampling with stratified random sampling in some specified populations, cluster sampling: equal cluster sampling, an estimator of mean and its variance, the relative efficiency of cluster sampling, optimum cluster size, and cluster sampling for proportions.
Course Outcomes
The students will learn some sampling methodologies that can be useful for inference purposes. The problem of inference in statistics is a major area of research, which has applications in many fields of study in real life.
Essential Reading
- R. K. Som, Practical Sampling Techniques, C R C Press
- William G. Cochran, Sampling Techniques, Wiley
Supplementary Reading
- S.K. Thompson, Sampling, John Wiley
- S.K. Thompson, Sampling, John Wiley