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Statistics for Biomedical Sciences

Module description

In this module you will explore statistical analysis of biomedical science data, and its use in establishing conclusions. The module aim is to familiarise you with various data analysis skills that can be utilise with biomedical science data. Through studying this module, you will gain hands-on experience in analysing biomedical datasets and develop an understanding of the advantages of employing statistical methods to comprehend and interpret data. You will use statistical analysis to make rational and justified decisions and develop new research hypotheses.  This module provides the foundation for all future higher modules in the degree programme. 

Module aims - intentions of the module

Scientific research is constantly evolving and generating vast quantities of data. By asking and answering scientific questions, data allow us to make robust conclusions and importantly, ask new questions. It is important that we have a strong understanding of how this information is generated and what it means. In this module, you will study how to use data to reach scientific conclusions and build upon existing knowledge. You will explore how to match appropriate statistical analyses to different study designs, and methods to control for biases. You will also learn how to decide which statistical methods are best suited to answering specific questions, based on their advantages and limitations. You will also learn to identify potential biases related to racial and social justice and apply equitable methodologies to ensure inclusive and representative findings. At the end of this module, you will be able to make informed decision on applying statistical analyses to interpret the data. You will also learn how to communicate your results in a clear and critical way. Assessment will take the form in class tests and a data analysis poster.

Graduate attributes: as part of this module, you will develop the key employability skills in teamwork, project management, and preparing and scientific communication.

The module aligns with sustainable development goals (SDGs) SDG 3 (Good Health and Wellbeing) ensuring knowledge into physiology and healthy lives along with SDG 5 (Gender Equality), SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure) and SDG 10 (Reduced Inequalities).

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Apply statistical concepts to address different kinds of scientific problems through testing of hypotheses.
• 2. Use statistical software to manipulate and display data on a variety of processes.
• 3. Use statistical software to analyse and interpret data, through the use of summary and inferential statistics.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 4. Formulate a valid research question that can be answered with quantitative data, and evaluate appropriate strategies to answer different kinds of research questions.
• 5. Evaluate data through a combination of graphical and statistical analysis.
• 6. Employ different methods to evaluate when data may be biased, and adjust for bias when this is possible
• 7. Use insight gained from data to develop specific suggestions for future lines of investigation.

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 8. Present your findings in graphical and textual ways to facilitate dissemination of complex ideas to a target audience.
• 9. Contextualise the results of statistical investigation within existing bodies of scientific knowledge.

Syllabus plan

Each week of teaching will introduce a new concept in statistics and data analysis. You will have a combination of lectures which introduce new topics, and practical workshop (in a computer room) when you will practice analysing and displaying data according to standard statistical techniques. You will work on real-life biological and biomedical datasets, and discuss topics of relevance to biomedical statistics, including possible sources of bias in data collection, and what we can do to correct them. The lectures and workshops will be supported by online quizzes (released every week) allowing you to test your understanding as you progress through the module.

The key concepts introduced in the module are different types of statistical tests, and how to choose the most suitable statistical test to answer different types of biomedical questions. This includes tests for frequencies (chi-square), means and medians (t-tests, ANOVA, and the non-parametric alternatives), correlation and regression. We will also learn about different methods to interpret and communicate results, with a particular focus on diagnostic tests and clinically important differences. This includes presenting data to the public in different ways, highlighting the difference between expert audiences (e.g. scientific papers) and non-expert audiences (e.g. policymakers, journalists, general public).

Accessibility statement:

All lectures for the module will be recorded and made available as captioned videos for asynchronous & remote access. The revision quizzes are available online and can be completed remotely at any time. The practical sessions for the module take place in a computing laboratory (of up to 80 students) and are typically 2 hrs in duration: these sessions are flexible in nature and students are welcome to take breaks (in or out of the laboratory) as and when needed. All instructions and tasks will be available online, and in the event of unavoidable absence, it is possible to complete all computer practical tasks remotely.

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

Deferral – if you miss an assessment for certificated reasons that are approved by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. If deferred, the format and timing of the re-assessment for each of the summative assessments is detailed in the table above ('Details of re-assessment'). The mark given for a deferred assessment will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral - if you have failed the module (i.e. a final overall module mark of less than 40%) and the module cannot be condoned, you will be required to complete a re-assessment for each of the failed components on the module. The format and timing of the re-assessment for each of the summative assessments is detailed in the table above ('Details of re-assessment'). If you pass the module following re-assessment, your module mark will be capped at 40%.

Indicative learning resources - Web based and electronic resources

Module ELE page containing formative quizzes and access to on-line learning resources

Key words search

Statistics, Data Analysis and Interpretation