Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems, hitting upon possible solutions.
The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample’s behavior and assess the elements of discrepancies.
Including case studies, exercises, and solutions, the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling, before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.
Table of Contents
Concepts of Population, Sample, Sampling, Interval and Point Estimation and Posing the Problem of Sampling. Size of Population, Size of Sample, Sampling Design, Sampling Scheme. Unequal Probability Sampling, Ratio-Estimation, Lahiri’s Sampling Scheme, Hartley-Ross Estimator. Stratified and Cluster Sampling. Super-Population Modeling, Prediction Approach, Model-Assisted Approach, and Bayesian Methods. Randomized Response and Indirect Questioning. Small Area Estimation. Network Sampling, Adaptive Sampling, Size Control, and Controlled Sampling. Analytical Surveys. Bibliography. Index.