MPH Occupational Health

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.

The course materials include worked examples, video demos, quizzes and practice tasks. Students are expected to work through the online course materials in their own time and use the discussion boards to ask questions and check their understanding of the course material.                                                                                                                                                                                                                                                                   Students on the On campus programme will also  need to be available for the face to face teaching/practical sessions that will be in the timetable. These will be delivered on campus at the University of Manchester. The same content will be delivered in webinars for online students. On Campus students are welcome to attend the webinars. All webinars will be recorded and shared on Canvas.

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).

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

• 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

The course materials are provided via the virtual learning environments Canvas and Articulate Rise. The course consists of 10 topics and within each topic there is a quiz or practical assignment 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 textbook 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 bi-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 bi-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. 

This is a mandatory course unit for students studying on the on-campus programme, or an optional course unit for students on the online programme. There are  written materials accessible online for all students which guide students through the course and include worked examples, video demos, quizzes and practice tasks. Students are expected to work through these materials in their own time. The lectures and webinars supplement the online resources.

There will be regular interaction with the tutors via the lectures and PC cluster practical sessions on the on-campus programme and  online through the webinars and  discussion boards. Students will be encouraged to use self-reflection to think about the ideas discussed, and take part in discussion board activities. Students should work through the unit in a logical sequence. The individual course unit timetables will guide what should be done and when. Participation in the discussion boards is greatly encouraged, and can help enhance your learning experience and prepare you for your assessment.

For all students - The majority of the course will be delivered through the virtual learning platform, which will include worked examples, video demos, quizzes,  required reading, practice assignments and discussion boards.  

Online students - There will be webinars that will be recorded to allow synchronous and asynchronous learning. Online students may join webinars live, but it is not mandatory. Recordings of all webinars be made available.

For on campus students - All face-to-face activities are mandatory for all students. Attendance is monitored and an escalation policy is in place for non-attendance. We also have weekly peer-led team study sessions where you will be asked to undertake tasks linked to the course unit materials using the discussion boards.

For all students - In line with guidance from the Office for Students and Quality Assurance Agency, the programme will be augmented by the Programme Director Seminar Series to deliver study skills, written English, academic writing, research skills,  critical thinking and understanding arguments, careers and employability skills, revision/assessment/examination skills including time management. 

• 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 

• Apply statistical thinking when conducting or reviewing research in professional practice.

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. 

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.