Umeå
The Ph. D. course Samplings, 4hp, will be given as a distance course.
Statistics I: Basic statistics, 4 hp or similar.
The objective of the course is to give a broad introduction to basic sampling theory and related statistical inference. The course is built on lectures, exercises and computer exercises. Exercises and computer exercises are mandatory.
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
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
Link to application
Course leader: Anton Grafström
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