Newcastle University

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.

This is an introduction to statistical concepts, and their use and relevance in health sciences. The main areas covered are descriptive statistics; probability concepts; hypothesis testing and confidence interval estimation; and interpreting and appraising the statistical content of research papers. A variety of techniques will be introduced within these areas, with the emphasis on when to use them, and how to interpret the results. Students will learn how to apply many of the techniques, and computer practical sessions (using MINITAB) will reinforce concepts and give practice in carrying out and interpreting statistical analyses.

Outline Of Syllabus

Graphical and numerical data summary; the Normal, Binomial and Poisson 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 commands to perform analyses.

Teaching Rationale And Relationship

The lectures and linked computer-based practicals and group work develop knowledge and module-specific skills. Module and key skills are developed through the course work and project used as part of the assessment.

Assessment Rationale And Relationship

Knowledge and understanding are assessed by the written examination. The project tests data analysis and presentation skills in addition to knowledge and understanding.