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  1. Welcome
  2. Course Outcomes
  3. Units in this Course
  4. Recommended Textbooks

Welcome

This is the complete study package for Sampling Techniques. The course covers the theory and practice of selecting samples from populations — Simple Random Sampling, Stratified, Systematic, Cluster — and a survey of India's official statistics bodies (NSO & NSC). Each concept has two worked examples.

Pre-requisite: The earlier subjects, especially basic estimation and sampling distributions from Theoretical Continuous Distributions and Inferential Statistics.

Course Outcomes

  1. Review population concepts, methods of data collection and types of errors.
  2. Get introduced to sampling schemes — simple, stratified, systematic.
  3. Understand how to conduct sample surveys and select the right scheme.
  4. Compare various sampling techniques on precision and efficiency.
  5. Use sampling tools to analyse real-world experimental data.

Units in this Course

UNIT 1

Sample Survey Concepts

Parameter vs statistic, sampling distribution; principal steps and principles of sample surveys; sampling vs non-sampling errors; types of sampling — subjective, probability, mixed.

 UNIT 2

Simple Random Sampling

SRSWR vs SRSWOR; lottery method & random-number method; estimators of population total & mean; variances; sample size determination; SRS for attributes.

 UNIT 3

Stratified Random Sampling

Definition, advantages & disadvantages; estimator of population mean & variance; proportional and optimum (Neyman) allocations; comparison with SRSWOR.

 UNIT 4

Systematic Sampling & More

Systematic sampling (\(N = nk\)), variance for linear trend, comparison with SRSWOR & Stratified; concepts of Cluster Sampling, Multistage Sampling and Quota Sampling.

 UNIT 5

National Statistical Office

NSO (NSSO & CSO) — vision, mission, roles, activities, publications; National Statistical Commission — need, constitution, role, functions and key acts.

 PRACTICAL

Practical Course (7 Experiments)

Verify unbiasedness of sample mean & mean square; SRSWR vs SRSWOR comparison; stratified allocation; precision comparisons; systematic sampling.

 REFERENCE

Official Syllabus

Course outline, textbooks, references and exam blueprint.
← Back to Course Hub Start with Unit 1 →

Next course in learning order: Sampling Theory Sampling & design