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MRes Primary Care (Web-based Learning) / Course details

Year of entry: 2020

Course unit details:
Practical Statistics for Population Health (formerly Biostatistics)

Unit code POPH60982
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Offered by Division of Population Health, Health Services Research and Primary Care
Available as a free choice unit? No


This course is relevant to current or future professionals whose careers will involve either conducting research or interpreting the findings of research studies. Statistical analysis of data is a key part of research and many research findings and recommendations are based on the results of statistical analysis. An awareness of statistical methods and the ability to interpret data from published studies is invaluable in a career in public health.

This is an interactive online course. Students must work through the online course material. Students are encouraged to use the Blackboard discussion boards to ask questions and check their understanding of the course material.


The aim of this course is to introduce you to statistical methods and to enable you to conduct basic statistical analyses within a statistical package.


Learning outcomes

On completion of this unit, successful students will be able to:
  • Distinguish between different data types
  • Present and summarise data using the appropriate techniques
  • Calculate population estimates for means and proportions
  • Calculate standard errors and confidence intervals for means and proportions
  • Conduct hypothesis tests for the comparison of two groups
  • Analyse categorical data
  • Conduct simple linear regression and correlation
  • Understand multiple linear regression and confounding
  • Understand the principles of logistic regression and survival analysis
  • Discuss the issues associated with sample size calculation
  • Be able to use a statistical software package


  • Types of data and summarising data
  • Probability distributions
  • Principles of statistics and statistical analysis
  • Confidence intervals
  • Hypothesis tests
  • Categorical data analysis
  • Correlation and simple linear regression
  • ANOVA and multiple linear regression
  • Logistic regression
  • Survival analysis

Teaching and learning methods

Online distance learning with course materials provided via the virtual learning environment Blackboard. The course consists of 10 topics and within each topic there is a self-test to complete. There are weekly discussion board topics and the discussion boards are moderated by the course unit leader and teaching assistants. The core text is referenced in each topic, and although you should be able to complete the topic adequately without the core text book we recommend that you obtain a copy as it will help you gain a deeper understanding of the subject. The course can be seen as a tutorial in using a statistical analysis package  and includes demonstrations of how to carry out statistical tests inusing the package. The course also includes the use of re-usable learning objects to convey some of the more complex statistical concepts.


Employability skills

Analytical skills
Students will develop their analytical skills by learning about statistical theory and learning how to analyse data using a range of statistical techniques.
Problem solving
Students will develop problem solving skills through learning how to choose the appropriate analysis technique to answer a particular research question as well as how to conduct the analysis using a statistical package and interpret the results of their analysis.
Students will develop quantitative research skills which will help students carry out statistical analysis of data collected in research studies.

Assessment methods

Assessment task

Weighting within unit (if relevant)

Midterm Assignment


Final Assignment



Feedback methods

Students will be provided with personalised feedback for their mid-term and final summative assignments, within 15 working days for mid-term assignments and 20 working days for final submission.
Further opportunities for formative feedback (on non-assessed work) will also be provided during a course unit. 

Study hours

Independent study hours
Independent study 150

Teaching staff

Staff member Role
Islay Gemmell Unit coordinator

Additional notes

For further information please watch this video from our Course Unit Leader:

If you have any questions about the content of this unit, please contact the course unit leader, Isla Gemmell, via email on If you have any other queries, please contact the PGT programme administrators via email on

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