# 2024/25 Taught Postgraduate Module Catalogue

## NUFF5040M Statistics for Health Sciences

### 15 creditsClass Size: 40

Module manager: Joseph Hicks, Matthew Mulvey
Email: J.P.Hicks@leeds.ac.uk; hssmmu@leeds.ac.uk

Taught: 1 Jan to 28 Feb View Timetable

Year running 2024/25

### Pre-requisite qualifications

Identical to student's parent taught postgraduate programme or PhD

 NONE

 NONE

### This module is mutually exclusive with

 NONE

Module replaces

None

This module is not approved as an Elective

### Module summary

The module provides students with the knowledge and skills necessary to 1) understand and critically interpret results from statistical analyses (as found in research literature), and 2) analyse health sciences data using statistical analyses. It will enable students to understand basic statistical concepts that are key to interpreting the results of statistical analyses. It will also equip students with skills to undertake valid statistical analyses, such as statistical inference, sample estimation, confidence intervals and p-values. Students will learn about study design, data types and statistical concepts. Through computer practicals using widely used statistical software students will learn how to undertake basic but versatile and powerful statistical analyses.

### Objectives

The purpose of the module is to:
- Introduce students to the fundamental statistical concepts and methods used in the health sciences
- Enable students to apply these concepts to understand and critically appraise the results of statistical analyses in the literature
- Enable students to undertake basic but versatile and powerful statistical analyses of data

Learning outcomes
- Classify, summarise and display data
- Demonstrate an understanding of how to interpret the results from a range of commonly used statistical analyses, including correctly interpreting confidence intervals and p-values
- Demonstrate an understanding of and be able to explain the difference between statistical and clinical significance
- Critically appraise the statistical findings in published research
- Based on a research question, devise a valid strategy for analysing a statistical dataset, undertake a valid analysis and present and interpret the results correctly and coherently

### Syllabus

- What are data and different types of data?
- Summarising data using statistics and presenting via tables and graphs
- Study design and sample size
- Basic probability distributions
- Estimation from a sample, including understanding statistical inference via confidence intervals and p-values
- Risk and summary measures for binary data
- Critical appraisal of statistical results
- Data processing
- Analysing continuous outcomes
- Analysing categorical outcomes

### Teaching methods

 Delivery type Number Length hours Student hours Class tests, exams and assessment 2 0.50 1.00 Group learning 4 1.00 4.00 Lecture 10 1.00 10.00 Practical 5 3.00 15.00 Private study hours 120.00 Total Contact hours 30.00 Total hours (100hr per 10 credits) 150.00

### Private study

Module pre-reading and directed exercises (12 hours)
- Basic mathematics refresher and test
- Directed background reading for key statistical concepts
During contact week (12 hours)
- Further directed reading and exercises
After contact week (96 hours)
- Formative assessment
- Summative assessment

### Opportunities for Formative Feedback

- Group feedback on directed exercises during the contact week (written)
- Group feedback on the class group work during the contact week (verbal)
- Individual and group feedback on computer exercises during the contact week (written and verbal)
- A formative assignment (draft summative assignment analysis and report plan) to be completed following the contact week, with individual written feedback provided before summative coursework due

### Methods of assessment

Coursework
 Assessment type Notes % of formal assessment Group Project Formative group work during the contact week with immediate feedback 0.00 Computer Exercise Formative computer exercises provided during computer practical sessions, with individual and group feedback provided during and at the end of practical sessions 0.00 Report Written report on the analysis of a dataset (max. 2,500 words) 100.00 Total percentage (Assessment Coursework) 100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated