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HSC8036 : Health Statistics

  • Offered for Year: 2022/23
  • Module Leader(s): Ms Vicky Ryan
  • Lecturer: Dr Michael Grayling, Professor James Wason, Professor Dawn Teare, Dr Jérémie Nsengimana
  • Other Staff: Dr Thomas Chadwick, Dr Theophile Bigirumurame
  • Owning School: FMS Graduate School
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 20
ECTS Credits: 10.0


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

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture231:0023:00Present in person: Lectures including interactive activities
Guided Independent StudyAssessment preparation and completion24:008:00Formative practice activities
Structured Guided LearningLecture materials121:0012:00Non-synchronous online
Structured Guided LearningAcademic skills activities231:0023:00Technical exercises and guided reading
Scheduled Learning And Teaching ActivitiesSmall group teaching31:003:00Present in person: Paper presentations
Scheduled Learning And Teaching ActivitiesSmall group teaching13:003:00Present in Person: Project introduction and preparation in small groups
Guided Independent StudyProject work301:0030:00N/A
Scheduled Learning And Teaching ActivitiesWorkshops101:0010:00Present in Person : Computer practicals - interactive activities around teaching
Scheduled Learning And Teaching ActivitiesDrop-in/surgery181:0018:00Present in person: Scheduled office hours until the project hand in date
Guided Independent StudyStudent-led group activity21:002:00Group paper presentation preparation
Guided Independent StudyIndependent study681:0068:00N/A
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 further developed through the technical exercises and the project which is used as the assessment.

Assessment Methods

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

Description Length Semester When Set Percentage Comment
Digital Examination601A40PIP Inspera invigilated MCQs
Other Assessment
Description Semester When Set Percentage Comment
Report1M602500 word report on an analysis of a large dataset
Assessment Rationale And Relationship

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

There are formative activities in the form of exercises (with outline answers) available for each session. There will be practice MCQs throughout the course and a mock MCQ exam.

Reading Lists