Sampling, 4hp

Prior knowledge

Statistics I: Basic statistics, 4 hp or similar.

Objective, including learning outcomes

The objective of the course is to give a broad introduction to basic sampling theory and related statistical inference. On completion of the course, the student will be able to:

• understand basic concepts of sampling from finite and infinite populations
• describe some basic sampling methods including conditions and assumptions 
• describe and apply basic estimators for survey sampling
• select an appropriate sampling method for a given problem
• carry out a basic probability sampling survey
• interpret and evaluate results from basic surveys correctly and draw reasonable conclusions
• clearly and concisely communicate results and conclusions
• use statistical software for sampling

Content

The main contents are as follows: 
• Simple random sampling
• Systematic sampling
• Cluster sampling
• Stratified sampling
• The Horvitz-Thompson estimator and unequal probability sampling
• Two-stage and two-phase sampling
• Basic point and plot sampling of an infinite population
• Line-intercept sampling 
• Detectability in sampling
• Line-transect sampling
• Capture-recapture estimation