Timetable information in the Course Catalogue may be subject to change.

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : Deanery of Molecular, Genetic and Population Health Sciences : Public Health Research

Postgraduate Course: Data Analysis for Epidemiology (PUHR11063)

Course Outline
SchoolDeanery of Molecular, Genetic and Population Health Sciences CollegeCollege of Medicine and Veterinary Medicine
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe course introduces the basic principles of statistical data analysis in an epidemiological context using the R programming environment for students who have already undertaken some introductory learning in the subject area.
Course description This course is designed to equip students who have already undertaken some learning in the principles of statistical methodology with a grounding in the practical skills of data analysis. The course will introduce good practice in data management and key skills in exploratory and inferential statistical analysis, using the open source R statistical programming language. Topics to be covered include numerical and graphical descriptive methods, simple one and two sample comparisons of categorical and continuous data using both confidence intervals and hypothesis tests, contingency tables and risk ratios, direct and indirect standardisation, correlation and simple linear regression as an introduction to general linear models.

The course (delivered online) will be based around 5 weekly case studies/ projects that will require students to undertake software-based analyses after using a mix of short recorded lectures and readings designed to illustrate each set of principles, with each week's activity building on the last. Each week, students will be encouraged to discuss their analysis plans, share useful code 'shortcuts' and discuss their results on the discussion boards. The case studies will be based on real epidemiological data sets and/ or common problems, although the principles will be applicable more broadly across a wide range of medical and scientific research.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesSuitable introductory statistics course equivalent to Epidemiology for Health Professionals (GLHE11016) - contact course organiser to check.
High Demand Course? Yes
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  None
Course Start Flexible
Course Start Date 05/08/2023
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 5, Seminar/Tutorial Hours 1, Online Activities 35, Feedback/Feedforward Hours 5, Formative Assessment Hours 5, Revision Session Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 46 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Feedback Students will receive formative feedback during the course
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Select and apply correct statistical methods for one and two sample problems with continuous and with categorical data
  2. Prepare data and perform: numerical and graphical summary techniques; assumption checking; and confidence interval and hypothesis testing
  3. Think critically about and solve common epidemiological statistical problems
  4. Use statistical software and interpret and communicate output
  5. Autonomously undertake your own basic epidemiological statistical analysis
Reading List
Additional Information
Graduate Attributes and Skills The skills developed by this course are key for most types of epidemiological enquiry, and thus fall broadly under the overarching Enquiry and Lifelong Learning attribute. In particular, the core tasks of analysis and project work involve problem solving, critical thinking and evaluation, which map closely to the Research and Enquiry cluster. However, this will also foster Personal and Intellectual Autonomy, contributing to the student's ability to conceive, design, execute and interpret epidemiological research.
Course organiserDr Niall Anderson
Tel: (0131 6)50 3212
Course secretaryMiss Lucy Courage
Tel: (0131 6)51 7111
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information