Short Courses in Applied Statistics

Course outline

Analysis of Variance (ANOVA) is a key technique popularly used in analysing research data. Every serious researcher needs to acquire skills in using this technique, and to have a good appreciation of the underlying concepts.

In this beginners' course, the theory, practice and interpretation of ANOVA in studies involving treatment (grouping) factors and in regression analysis will be explained. The General Linear Model (GLM) on which the ANOVA is based will be discussed in order to demonstrate how ANOVA can be used to deal with more complex situations.

Computer-based practical sessions using appropriate statistics software (Genstat, Minitab, SAS, SPSS or Stata) will give participants the skills needed to apply ANOVA ideas. Data from a variety of scientific disciplines will be used to illustrate the analysis with emphasis on the interpretation of output in relation to study objectives.

Who should attend?

Scientists and technologists. Participants will be assumed to have working knowledge of the basic principles of statistical methodology such as estimation, confidence intervals and hypothesis testing.

How you will benefit

This two-day course will give you a firm grounding in the principles underlying analysis of variance, and an appreciation of how the basic techniques can be extended to more complex real life situations.

Course content

A review of basic statistical methodology
Analysis of variance for comparing several means
Analysis of variance for exploring simple relationships
Taking account of additional sources of variation (blocking ideas)
Linear modelling ideas to illustrate extensions to more complex situations
Checking ANOVA assumptions via a study of residuals