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Course unit details:
Practical Statistics for Population Health
Unit code | POPH60982 |
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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 |
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 important for a career in public health.
Students choosing Practical Statistics for Population Health will need to be available for the face to face/online teaching sessions that will be in the timetable. These will be delivered on campus at the Univeristy of Manchester as well as online. This is an interactive online course. Students musts 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.
Pre/co-requisites
This unit is mandatory for the Dental Public Health stream.
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
The course materials are 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.
SPSS is a menu driven statistical software which is available via a licence code for which there are some restrictions for distance learning students, R is free and open-source, and can be installed on any computer.
On campus students only
You are expected to attend weekly lectures and other face to face activities. Access to the SPSS software will be available via the PC clusters on campus.
Distance/blended learning students only
You will be able to attend weekly webinars which will be recorded. You will download the SPSS software through a secure link from the UoM managed platform ZendTo unless you are a national of a USA embargoed country (see additional notes below) in which case you must use the R software.
Knowledge and understanding
- 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.
Intellectual skills
- 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.
Practical skills
- Use a statistical package to analyse a data set
Transferable skills and personal qualities
- Apply statistical thinking when conducting or reviewing research in professional practice.
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
Method | Weight |
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Written assignment (inc essay) | 100% |
Written assignment (reporting the results of statistical analysis of data set). Final assignment worth 100% of marks – 2500 – 3000 words or equivalent.
Feedback methods
Further opportunities for formative feedback (on non-assessed work) will also be provided during the course unit.
Recommended reading
The core text for the course is: Essential Medical Statistics by Kirkwood and Sterne (2003).
All students should have access to an electronic copy of this book via Koretext which can be accessed via the 'Reading Lists Online' link on the menu in Blackboard.
Another useful introductory textbook is An Introduction to Medical Statistics by Martin Bland (2000) (Bland M., 2000).
Students may find the Statistics at Square One website helpful during the course.
Study hours
Scheduled activity hours | |
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Practical classes & workshops | 16 |
Independent study hours | |
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Independent study | 134 |
Teaching staff
Staff member | Role |
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Islay Gemmell | Unit coordinator |
Additional notes
If you have any questions about the content of this unit, please contact the course unit leader, Isla Gemmell, via email at isla.gemmell@manchester.ac.uk. If you have any other queries, please contact the PGT programme team at shs.programmes@manchester.ac.uk.
Embargoed country list
- Afghanistan
- Belarus
- Burma
- Cambodia
- Central African Republic
- China
- Democratic Republic of Congo
- Cuba
- Cyprus
- Eritrea
- Haiti
- Iran
- Iraq
- Lebanon
- Libya
- North Korea
- Russia
- Somalia
- Republic of South Sudan
- Sudan
- Syria
- Venezuela
- Zimbabwe
Online distance learning students who are nationals of these countries cannot download and install SPSS on their own devices and therefore must use the R software to complete the course.