STA304H5 • Surveys, Sampling and Observational Data

Description

The sample survey is a widely used technique for obtaining information about a large population at relatively small cost. Only probability samples can provide both an estimator and a measure of sampling error from the data itself. In addition to sampling error, non-sampling errors (refusals, not-at-home, lies, inaccuracies, etc.) are always present, and can produce serious biases. The course covers: design of surveys, sources of bias, randomized response surveys. Techniques of sampling; stratification, clustering, unequal probability selection. Sampling inference, estimates of population mean and variances, ratio estimation, observational data; correlation vs. causation, missing data, sources of bias.

Prerequisites
Exclusions
Enrolment Limits
Priority is given to students enrolled in Statistics Specialist or Major programs.
Distribution Requirement
Science
Total Instructional Hours
36L/12T
Mode of Delivery
In Class
Program Area
Statistics, Applied