# HAR6045: Further Statistics for Health Science Researchers

The Further Statistics for Health Science Researchers module is led by Jeremy Dawson. It runs in the Spring semester and is worth 15 credits.

### Overview

The Further Statistics for Health Science Researchers module is led by Jeremy Dawson. It runs in the Spring semester and is worth 15 credits.

It is one of the modules on:

• Master of Public Health (Health Services Research) (option)
• Master of Public Health (MPH) (option)
• MSc Clinical Research (NIHR for Academic Clinical Fellows) (option)
• MSc Clinical Research (standard route) (option)
• MSc Human Nutrition (option)

This module is available as a CPD option

This module is available Department-wide in any year as a DDP module

It is necessary to complete HAR6035 or HAR6039 successfully before progressing to study on this module. Cannot be taken with HAR6061.

### Introduction

The module will cover fundamental statistical concepts, and both simple statistical methods and the more widely used advanced methods of multiple regression, survival analysis and generalised linear models.

It will be a practical module, including the teaching of the statistical software SPSS.

The module equips students with the knowledge and skills necessary to design and analyse a study to answer specific research questions, understand and critically appraise the literature, and to present research findings in a suitable fashion.

It is necessary to complete HAR6035, HAR6039 or HAR6042 successfully before progressing to study on this module.

### Objectives

This unit aims to:

• introduce students to fundamental concepts and modern analysis methods in statistics used by health science researchers
• enable students to apply these concepts to critically appraise research literature
• equip students with the knowledge and skills necessary to appropriately analyse a study using SPSS; and to present research findings in a suitable fashion

### Learning outcomes

By the end of the unit, a student will be able to:

• Classify and appropriately display and summarise different types of data
• Describe and test statistical hypotheses in an appropriate manner
• Analyse data appropriate to the particular study design
• Understand parametric and non-parametric tests and when they should be used
• Understand how to use multiple linear regression
• Understand how to use logistic regression and other generalised linear models
• Understand how to use survival analysis
• Use SPSS to perform all of the above analyses and to manage data
• Evaluate the quality of published research from recent papers

### Teaching methods

Lectures will be used to impart knowledge of key statistical concepts and methods, while structured exercise classes will apply these concepts to example data or published studies.

The content of our courses is reviewed annually to make sure it is up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research, funding changes, professional accreditation requirements, student or employer feedback, outcomes of reviews, and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

Information last updated: 15 June 2022