Aims

To explain the relevance of statistical ideas and techniques to health sciences.
To introduce the requirements, advantages and disadvantages of the techniques covered in the module, and hence identify an appropriate statistical technique for a situation.
Enable students to interpret the results of statistical analyses reported in the literature and carry out and interpret simple statistical analyses using appropriate software.

Outline Of Syllabus

This is an introduction to statistical concepts, and their use and relevance in health sciences. The emphasis will be on when to use particular techniques, and how to interpret the results. Students will learn how to apply many of the techniques, and computer practical sessions will reinforce concepts and give practice in carrying out and interpreting statistical analyses. Topics covered are graphical and numerical data summary; the Normal, and Chi-squared distributions; combining probabilities; confidence intervals and hypothesis tests for comparing means and proportions; transformations and non-parametric tests; simple correlation and linear regression; confounding and effect modification; ANOVA and multiple comparisons; survival analysis; simple linear and logistic regression; sample size calculations; MINITAB and EPI INFO commands to perform analyses.

Teaching Rationale And Relationship

The lecture materials and linked computer-based practical sessions and group work develop knowledge and module-specific skills. Module and key skills are developed through the course work and the project which is used as the assessment.

Assessment Rationale And Relationship

The project will test the students' data analysis and presentation skills in addition to their knowledge and understanding of statistical methods and the ability to interpret the results of analyses.

There are formative activities in the form of exercises (with outline answers) available for each session.