Time Schedule:
John R. Skalski
Q SCI 480
Seattle Campus
Theory and applications of sampling finite populations including: simple random sampling, stratified random sampling, ratio estimates, regression estimates, systematic sampling, cluster sampling, sample size determinations, applications in fisheries and forestry. Other topics include sampling plant and animal populations, sampling distributions, estimation of parameters and statistical treatment of data. Prerequisite: Q SCI 482; recommended: Q SCI 483. Offered: jointly with STAT 480; W, odd years.
Class description
Theory and applications of sampling finite populations including: simple random sampling stratified random sampling, ratio estimates, regression estimates, systematic sampling, cluster sampling, sample size determinations, applications in fisheries and forestry. Other topics include sampling for hot spots, rotational or panel designs, and line-transect sampling.
Student learning goals
Basic finite sampling theory with special applications to environmental and ecological scenarios
Meaning of sampling precision and sample size calculations
Relationships between finite populations, sampling frames, and statistical inferences
Relationship between how a sample size is drawn, estimators, and their variance calculations
General method of instruction
Two 1.5-hour lectures per week, weekly assignments, and daily readings. Two alternative textbooks.
Recommended preparation
Working knowledge of statistical methods and inferences, as taught in QSCI 482, essential.
Class assignments and grading
Nine weekly homework assignments analyzing ecological data and/or structuring sample surveys. Final project involves designing, conducting, analyzing, and reporting of a finite survey conducted by the student.
Grade based on total numerical score from nine weekly homework assignments (450 points) and final course project (150 points).
