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

Year of entry: 2021

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Course unit details:
Practical Statistics for Population Health

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

Overview

This course is relevant to current or future professionals whose careers will involve either conducting quantitative research or interpreting the findings of quantitative 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.

Aims

The aim of this course unit is to provide students with an understanding of statistics that they can apply within their own professional practice. This could include conducting quantitative research, interpreting the findings of quantitative research studies or applying statistical thinking to public health practice. The course will teach you how to conduct statistical analyses using a statistical package (SPSS or R).

Learning outcomes

On completion of this unit, successful students will be able to:

  • Apply statistical thinking when conducting or reviewing research in professional practice.
  • Demonstrate an understanding of the relationship between populations, samples and variability in research studies.
  • Define different types of data and demonstrate an understanding of confidence intervals and the normal distribution.
  • Perform correlation and simple linear regression and interpret the results.
  • Construct and interpret multiple regression models and logistic regression models demonstrating an understanding of confounding.
  • Demonstrate the use of methods for statistical inference.
  • Perform and interpret survival analyses.
  • Use a statistical package to analyse a data set

Syllabus

Introduction to statistical thinking

Types of data

Populations and sampling, variability and sample size

The normal distribution and confidence intervals

Correlation and simple linear regression

Multiple regression

Logistic regression

Statistical inference for continuous and categorical data

Survival Analysis

Statistics in Practice

Teaching and learning methods

Online distance learning with course materials provided via the virtual learning environments Blackboard and Articulate Rise. 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 (SPSS or R) and includes demonstrations of how to carry out statistical tests in these packages.

Employability skills

Analytical skills
Students will develop their analytical skills by learning how to conduct statistical analyses using a statistical package and how to interpret the results of their analysis.
Problem solving
Students will develop problem solving skills through developing their skills in statistical thinking.
Research
Students will develop skills in conducting quantitative research and interpreting the findings of quantitative research studies.

Assessment methods

Assessment task

Weighting within unit (if relevant)

Midterm Assignment

30%

Final Assignment

70%

 

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: https://video.manchester.ac.uk/faculties/edfa2331ca0cd9a14d717cb1d233466f/ca24dc84-09b1-41b6-827e-d852d22d2ee8/

If you have any questions about the content of this unit, please contact the course unit leader, Isla Gemmell, via email on isla.gemmell@manchester.ac.uk. If you have any other queries, please contact the PGT programme administrators via email on mph.admin@manchester.ac.uk

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