Sampling theory and methods

Sampling Theory and Methods presents the theoretical aspects of "Sample Surveys" in a lucid form for the benefit of both undergraduate and post graduate students of Statistics. It assumes very little background in probability theory.

The author presents in detail several sampling schemes, including simple random sampling, unequal probability sampling, and systematic, stratified, cluster, and multistage sampling. In addition to sampling schemes, he also discusses several estimating methods, such as ratio and regression estimators, and covers in detail the use of superpopulation models.Many solved theoretical problems are incorporated into almost all the chapters. This feature helps readers acquire necessary skills to solve theoretical problems on their own.

PRELIMINARIES
Basic Definitions
Estimation of Population Total
Problems and Solutions
EQUAL PROBABILITY SAMPLING
Simple Random Sampling
Estimation of Total
Problems and Solutions
SYSTEMATIC SAMPLING SCHEMES
Introduction
Linear Systematic Sampling
Schemes for Populations with Linear Trend
Autocorrelated Populations
Estimation of Variance
Circular Systematic Sampling
Systematic Sampling in Two Dimensions
Problems and Solutions
UNEQUAL PROBABILITY SAMPLING
PPSWR Sampling Method
PPSOE Sampling Method
Random Group Method
Midzuno Scheme
PPS Systematic Scheme
Problems and Solutions
STRATIFIED SAMPLING
Introduction
Sample Size Allocation
Comparison with Other Schemes
Problems and Solutions
USE OF AUXILIARY INFORMATION
Introduction
Ratio Estimation
Unbiased Ratio Type Estimators
Almost Unbiased Ratio Estimators
Jackknife Ratio Estimator
Bound for Bias
Product Estimation
Two Phase Sampling
Use of Multi-Auxiliary Information
Ratio Estimation in Stratified Sampling
Problems and Solutions
REGRESSION ESTIMATION
Introduction
Difference Estimation
Double Sampling in Difference Estimation
Multivariate Difference Estimator
Inference under Super Population Models
Problems and Solutions
MULTISTAGE SAMPLING
Introduction
Estimation under Cluster Sampling
Multistage Sampling
NON-SAMPLING ERRORS
Incomplete Surveys
Randomised Response Methods
Observational Errors
RECENT DEVELOPMENTS
Adaptive Sampling
Estimation of Distribution Functions
Randomised Response Methods for Quantitative Data
REFERENCES
INDEX