Postgraduate

HSC8036 : Health Statistics

Semesters
Semester 1 Credit Value: 20
ECTS Credits: 10.0

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 Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials71:007:00Non-synchronous online: including practice formative activities
Guided Independent StudyDirected research and reading181:0018:00N/A
Structured Guided LearningAcademic skills activities11:001:00Non-synchronous online: Computer practical
Guided Independent StudySkills practice181:0018:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching81:008:00Synchronous online: including practice formative activities
Scheduled Learning And Teaching ActivitiesSmall group teaching31:003:00Synchronous online: Paper presentations
Scheduled Learning And Teaching ActivitiesSmall group teaching13:003:00Synchronous online: Project introduction and preparation in small groups
Scheduled Learning And Teaching ActivitiesWorkshops43:0012:00Present in person: Teaching, interactive activities, computer practical
Guided Independent StudyProject work301:0030:00N/A
Scheduled Learning And Teaching ActivitiesWorkshops21:002:00Synchronous online: Computer practical: interactive activities around teaching
Guided Independent StudyReflective learning activity181:0018:00N/A
Scheduled Learning And Teaching ActivitiesDrop-in/surgery111:0011:00Synchronous online: scheduled office hours
Guided Independent StudyIndependent study691:0069:00N/A
Total200:00
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 Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report1M1003000 word report on an analysis of a large dataset (including team design of a study)
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.

Reading Lists

Timetable