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.

Students will learn 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,

The students will learn 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,

The students will learn Estimation of gain in precision due to stratification, Systematic random sampling: Sample selection procedure, Advantages and disadvantages, Estimation mean and its sampling variance,

The students will learn a 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.

1. The students will have sound knowledge of the 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, stratified random sampling: Procedure for selecting a random sample.

2. The students will have a sound knowledge on 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, Allocation of sample size in different strata, Relative precision of stratified random sampling over simple random sampling,

3. The students will be equipped with the Estimation of gain in precision due to stratification, Systematic random sampling: Sample selection procedure, Advantages and disadvantages, Estimation means, and sampling variance.

4. The students will understand the problems 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.

R.K.Som, Practical Sampling Techniques, CRC Press, 1995.

William Gemmell Cochran, Sampling Techniques, Wiley

S.K. Thompson, Sampling, John Wiley

S.K. Thompson, Sampling, John Wiley