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DRPS : Course Catalogue : Deanery of Molecular, Genetic and Population Health Sciences : Public Health Research

Postgraduate Course: Principles of Epidemiology and Statistics (PUHR11105)

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 AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis course introduces the fundamentals of epidemiology, providing students with an understanding of different epidemiological concepts, approaches and investigative methods, and essential statistical skills. It focuses on: how to measure health and disease; the core epidemiological concepts of chance, bias and confounding; and the most commonly used epidemiological study designs. It also introduces students to core statistical concepts, such as data distribution, hypothesis testing and data visualisation, as well as a range of statistical tests and measures.
Course description The Principles of Epidemiology and Statistics course is designed to be engaging and informative to people at all levels, whether just beginning to work with epidemiology or for those who have a basic grasp but wish to extend their knowledge further. It assumes no prior knowledge of epidemiology or statistics. This course equips students with an understanding of the principles and application of fundamental epidemiological and statistical concepts, thus preparing students for subsequent intermediate-level epidemiology and statistics courses.

The course concentrates on the following areas:
- measures of disease frequency
- basic statistical concepts used in epidemiology
- interpretation of basic statistical results of epidemiological studies
- the uses, advantages and disadvantages of commonly used epidemiological study designs
- sources of error in epidemiological studies (chance, bias and confounding)
- critical appraisal skills for epidemiology
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2023/24, Available to all students (SV1) Quota:  None
Course Start Flexible
Course Start Date 05/08/2023
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 10, Seminar/Tutorial Hours 2, Online Activities 70, Feedback/Feedforward Hours 10, Formative Assessment Hours 10, Revision Session Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 92 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Feedback Students will receive formative feedback on set activities, via the discussion board, written feedback on the formative and assessed assignments via turnitin.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate a critical understanding of key epidemiological and statistical concepts, with particular focus on topics such as study design strengths and weaknesses, chance, bias and confounding
  2. Apply such knowledge to critically appraise epidemiological studies from the perspectives of design, execution and analysis
  3. Communicate concepts and critiques clearly to a specialist or peer audience
Reading List
A reading list will be provided on the course virtual learning environment.
Additional Information
Graduate Attributes and Skills 1) Generic cognitive skills. Students will critically engage with epidemiological and statistical principles and concepts. They will apply this understanding to critically appraise epidemiological literature and to further develop critical thinking skills.

2) Communication, ICT and numeracy. Students will develop communication skills with their peers and senior colleagues through discussion tasks, group work and assessments. Students will develop and apply basic statistical understanding to critically evaluate a range of numerical and graphical data.

3) Autonomy, accountability and working with others. Students will develop skills in and capacity for self-directed learning. Students will take responsibility for their own work.
Course organiserDr Regina Prigge
Course secretaryMiss Lucy Courage
Tel: (0131 6)51 7111
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