The Department of Mathematics and Statistics

Course Description

This course aims to deliver basic ideas of sampling and experimental design from an applied perspective and to provide experience with real-like problems and data. The course will cover the main techniques used in actual sampling practice — simple random sampling, stratification, systematic selection and cluster sampling.

This is an applied statistical methods course. It differs from most statistics courses because it is concerned as much with the design of data collection as with the analysis of data. The course will concentrate on problems of applying sampling methods to human populations, because survey practices are widely used in that area, and because sampling human populations pose particular problems not found in sampling of other types of units. However, the principles of sample selection can be applied to many other types of populations.

The experimental designs covered are sufficient to provide students with the knowledge and capability to execute and advise on experiments in and of the sciences. Students get exposure to the analysis of real datasets using appropriate statistical software like SPSS and R to analyze survey data.

Assessment