HSC8036 : Health Statistics (Inactive)
- Inactive for Year: 2025/26
- Module Leader(s): Ms Vicky Ryan
- Lecturer: Dr Jérémie Nsengimana, Dr Jingky Lozano-Kuehne, Professor James Wason
- Other Staff: Dr Thomas Chadwick, Miss Dorcas Kareithi
- Owning School: Population Health Sciences
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
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; 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; multiple linear regression and logistic regression; sample size calculations; STATA commands to perform analyses.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Structured Guided Learning | Lecture materials | 12 | 1:00 | 12:00 | Non-synchronous online |
| Guided Independent Study | Assessment preparation and completion | 1 | 29:00 | 29:00 | Preparing for and completing and online multiple choice exam. |
| Scheduled Learning And Teaching Activities | Lecture | 23 | 1:00 | 23:00 | Present in person: Lectures including interactive activities |
| Guided Independent Study | Assessment preparation and completion | 1 | 16:00 | 16:00 | Preparing for and completing a written report on the analysis of a large data set. |
| Structured Guided Learning | Academic skills activities | 23 | 1:00 | 23:00 | Technical exercises and guided reading |
| Scheduled Learning And Teaching Activities | Small group teaching | 1 | 3:00 | 3:00 | Present in Person: Project introduction and preparation in small groups |
| Scheduled Learning And Teaching Activities | Small group teaching | 3 | 1:00 | 3:00 | Present in person: Paper presentations |
| Scheduled Learning And Teaching Activities | Workshops | 10 | 1:00 | 10:00 | Present in Person : Computer practicals - interactive activities around teaching |
| Guided Independent Study | Student-led group activity | 2 | 1:00 | 2:00 | Group paper presentation preparation |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 18 | 1:00 | 18:00 | Present in person: Scheduled office hours until the project hand in date |
| Guided Independent Study | Independent study | 61 | 1:00 | 61:00 | N/A |
| Total | 200:00 |
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 further developed through the formative exercises and the project which is used as the assessment.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Digital Examination | 60 | 1 | A | 40 | PIP Inspera invigilated MCQs |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 1 | M | 60 | 2000 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
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- HSC8036's Timetable