STA632 : Sampling Techniques

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Course Info

Course Category

Probability & Statistics

Course Level

Undergraduate

Credit Hours

3

Pre-requisites

N/A

Instructor

Dr. Muhammad Noor-Ul-Amin
PhD Statistics
National College of Business & Economics, Lahore

Course Contents

Sampling and non-Sampling errors, Probability Sampling, Non-Probability sampling, Simple Random sampling, Stratified random sampling, Systematic sampling, Cluster Sampling, Sampling with R, Estimation of sample size for mean estimation, Estimation of proportion, Confidence interval, Optimum allocation, Comparison of allocation methods, Proportional allocation with SRS example, Neyman allocation with SRS example, Systematic sampling using R, Estimation in cluster sampling, Variance of sample mean in cluster sampling, Comparison between SRS and cluster sampling, Cluster sampling for unequal cluster sizes, Weighted mean for unequal cluster, Cluster sampling example with R, Hansen Hurwitz estimator, Lahir’s method, Horvitz Thompson Estimator, Estimation of mean with auxiliary variable, Ratio estimator, Hartley Ross Unbiased ratio estimator, Regression Estimator, Small population example for ratio estimator, Ratio estimator using R, Product estimator, Separate type regression estimator, Double sampling using R, Two-stage sampling, Rank set sampling, Non-response with R, Qualitative Randomized Response technique, RRT with R for Qualitative sensitive variable, Ratio estimator with two random variables, Regression Estimator with two random variables, Capture recapture sampling, Line and Point transects, Adaptive cluster sampling