Module manager: Dr Kate Best
Email: K.E.Best@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2025/26
See programme entry requirements
This module is not approved as an Elective
The ability to capture and handle data is essential in health and social care research. This module builds upon the key concepts introduced in MEDR5310M Getting started in health research. In this module you will explore a range of topics relating to capturing and handling quantitative and qualitative health and social care data. You’ll be introduced to the advantages and disadvantages of different sources of quantitative health data including Electronic Health Records, established longitudinal cohort studies and disease registers. You will be introduced to descriptive statistics (distributions, central measures and spread) and epidemiological terms (crude, category specific and standardized incidence and prevalence, odds and risk). You will undertake practical sessions in statistical software, where you will produce descriptive statistics based on a health dataset and learn how to best present the results in tables and figures. You will also learn about qualitative data and how to best display it. Finally you will be introduced to the concept of mixed methods research. By the end of this module you will be able to derive appropriate epidemiological terms and descriptive statistics using a statistical software, and you will have an understanding of qualitative data and how to display it.
The teaching style for this module is active and participative. The module will include a series of lectures and seminars with practical activities and computer practical sessions.
Through lectures you will be introduced to different health data sources, and in group-based discussions you will learn about the important strengths and weaknesses of these data sources.
Through lectures you will be introduced to epidemiological terms: odds, risk, incidence, prevalence and standardised mortality ratios. Practical sessions will include calculation of odds and risk from 2x2 tables, calculation of age and sex specific incidence, calculation of age standardised incidence and standardised mortality ratios.
Through lectures, group-based discussions and an interactive statistics quiz, you will learn to identify different types of quantitative variables, which summary statistics are most appropriate for summarising these variables.
Through an interactive work-book session you will learn how to define and calculate scale and test metrics such as sensitivity, specificity, positive predictive value and negative predictive value. Through the practical session you will learn how these metrics are related.
Thorough computer practical sessions you will learn how to manipulate a data set and how to produce descriptive statistics.
Through lectures and group-based activities you will gain understanding of qualitative data and how to display it, and you will be introduced to mixed methods research design.
On successful completion of the module and associated assessment, you will have demonstrated the following learning outcomes relevant to the subject:
1- Evaluate the optimum descriptive (summary) statistics (e.g. mean, standard deviation, median, inter-quartile range) to describe different types of quantitative data, taking into account the distribution of that data.
2- Analyse quantitative data using a statistical software by calculating the appropriate descriptive statistics.
3- Create tables and figures of your analyses that are appropriate for a peer-reviewed journal article
4- Apply your understanding of qualitative research to critically appraise qualitative studies
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
1- To demonstrate the ability to understand, interpret, analyse and manipulate numerical data, using a statistical software package; applying the ‘work ready’ (problem solving/ analytical) and ‘digital’ (digital creation, problem-solving & innovation) skills outlined in the Leeds Skills Matrix
2- Demonstrate an ability to communicate quantitative data analysis findings clearly and concisely in a written format, applying the ‘academic’ skills (presentation skills, academic writing, academic language) outlined in the Leeds Skills Matrix.
3- Critically appraising published qualitative journal articles applying the ‘work ready’ (critical thinking) and ‘academic’ skills (presentation skills, academic writing, academic language) outlined in the Leeds Skills Matrix.
This module will include topics on:
- Calculating and interpreting risk, odds, incidence (including age standardising) and prevalence
- Descriptive statistics, including central measures and spread for different types/ distributions of data
- Introduction to statistical software
- Mixed method research
- Critical appraisal of published qualitative research
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 2 | 1.5 | 3 |
| Practical | 1 | 0.5 | 0.5 |
| Practical | 1 | 1.5 | 1.5 |
| Practical | 1 | 2.5 | 2.5 |
| Seminar | 1 | 1 | 1 |
| Seminar | 1 | 3.5 | 3.5 |
| Seminar | 2 | 2 | 4 |
| Seminar | 3 | 1.5 | 4.5 |
| Private study hours | 129.5 | ||
| Total Contact hours | 20.5 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Small group work and practical sessions with tutor support will take place throughout the module. During practical sessions and seminars, you will work in groups to address different tasks- which will enable feedback and discussion (with a tutor on hand to contribute). At the end of these sessions you will often present your group work to the rest of the class to enable further and wider discussion with teaching staff. This will provide formative feedback on writing and ability to communicate findings clearly and concisely. These are skills that will be assessed in summative assessments.
On the final day of teaching you will have the opportunity for feedback from your tutor and peers via the statistics quiz. You will answer multiple choice questions on the statistics quiz and then your tutor will facilitate a discussion with the class and provide the correct answers. This will provide feedback on your understanding of summary statistics, data distribution and data types which will then be assessed in the summative assignment.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | Formative assessment - Statistics quiz | 0 |
| Coursework | Descriptive (summary) statistics task | 50 |
| Coursework | Critical appraisal of published qualitative research | 50 |
| Total percentage (Assessment Coursework) | 100 | |
Resits will be of the same format as the original piece of coursework. Students must receive a pass in both components of the coursework to pass the module overall (i.e. compensation across components is not allowed). Module marks will be capped at 50% on successful resit of any failed assessment in the module.
The reading list is available from the Library website
Last updated: 01/04/2025
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