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Source document. This page reproduces the syllabus this course was written to, as published — its semesters, credits and paper numbers are that document’s, not this site’s. The course itself is studied on its own, in any order.

This page reproduces the prescribed outline for the theory paper and for Section B of its practical, so that the teaching pages can be checked against it line by line. It is the syllabus, not a summary of it. Nothing about marks, duration or examination pattern appears on this site.

Course Objectives

  1. To understand the estimators used to estimate population parameters (Mean, variance, Ratio and Regression) when the sample is drawn using various sampling methods (SRSWR, SRSWOR, Stratified, Systematic, Cluster and two stage sampling).
  2. In conducting sample survey Using SRS, methods.
  3. To estimate the parameters of population and estimating variances.

Course Outcomes

  1. Able to form the questionnaire for conducting survey and knowing sampling and non-sampling errors involved in it.
  2. Able to design a sample survey to conduct using various sampling methods.
  3. Able to estimate the population parameters based on the sample statistic when sample collected using various methods.

Stated Pre-requisite

ASSUMED BEFORE THIS PAPER

Basic terminology, Need & Principal steps in sample surveys, census versus sample surveys, sampling and non-sampling errors, sampling methods. SRSWR, SRSWOR, stratified and systematic sampling methods, estimates of their population mean, variances etc.

Covered by Sampling Techniques, Units 1 to 4.

Unit I

AS PRESCRIBED

Review Unequal Probability Sampling: PPSWR/WOR methods (including Lahiri's scheme) and related estimators of a finite population mean. Horowitz – Thompson, Hansen – Horowitz and Yates and Grundy estimators for population mean/total and their variances.

→ Unit 1 notes

Unit II

AS PRESCRIBED

Ratio Method Estimation: Concept of ratio estimators, Ratio estimators in SRS, their bias, variance/MSE. Ratio estimator in Stratified random sampling – Separate and combined estimators, their variances/MSE.

Regression method of estimation: Concept, Regression estimators in SRS with pre – assigned value of regression coefficient (Difference Estimator) and estimated value of regression coefficient, their bias, variance/MSE, Regression estimators in Stratified Random sampling – Separate and combined regression estimators, their variance/MSE.

→ Unit 2 notes

Unit III

AS PRESCRIBED

Cluster Sampling: Cluster sampling with clusters of equal sizes, estimator of mean per unit, its variance in terms of intra cluster correlation, and determination of optimum sample and cluster sizes for a given cost. Cluster sampling with clusters of unequal sizes, estimator – population mean its variance/MSE.

→ Unit 3 notes

Unit IV

AS PRESCRIBED

Sub-Sampling (Two-Stage only): Equal first stage units – Estimator of population mean, variance/MSE, estimator of variance. Determination of optimal sample size for a given cost. Unequal first stage units – estimator of the population mean and its variance/MSE. Non – Sampling errors: Sources and treatment of non-sampling errors. Non – sampling bias and variance. Randomized Response Techniques (for dichotomous populations only): Warner's model, unrelated question model. Small area estimation: Preliminaries, Concepts of Direct Estimators, Synthetic estimators and Composite estimators.

→ Unit 4 notes

Practical Paper STS-206, Section B — List of Practicals

The practical paper is Designs and Analysis of Experiments and Sampling Theory (Conventional). Section B belongs to this paper; Section A belongs to Design and Analysis of Experiments (STS-203).

  1. PPS sampling with and without replacements.
  2. Ratio estimators in SRS, comparison with SRS.
  3. Separate and combined ratio estimators, Comparison.
  4. Regression estimators in SRS, Comparison with SRS and Ratio estimators.
  5. Separate and combined Regression estimators, Comparison.
  6. Cluster sampling with equal cluster sizes.
  7. Sub sampling (Two–stage sampling) with equal first stage units.

→ Practical notes, Section B

References

  1. Parimal Mukhopadhyay (2015): Theory and Methods of Survey Sampling, PHI.
  2. Murthy, M. N. (1967): Sampling Theory and Methods, Statistical Publishing Society.
  3. Des Raj (1976): Sampling Theory, Tata McGraw Hill.

Two names above are printed with spellings that differ from the published works: the syllabus writes “Horowitz – Thompson” for the Horvitz–Thompson estimator and “Hansen – Horowitz” for Hansen–Hurwitz. The teaching pages use the published spellings.

← Sampling Theory Unit 1 →