HAR6061: Further Statistics for Health Science Researchers (online)

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

It is one of the modules on:

This module is available as a CPD option

This module is available as a DDP module

Cannot be taken with HAR6045. To take this module students must have successfully passed HAR6035, HAR6039, HAR6042 or an equivalent introductory-level statistics module.


Introduction

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

It will be a practical module, including the teaching of the statistical software SPSS, equipping students with the knowledge and skills necessary to design and analyse a study to answer specific research questions; to understand and critically appraise the literature more thoroughly; and to present research findings in a suitable fashion.

This module is for distance-learning (DL) students, and MSc Clinical Research students whose clinical work prevents them taking the equivalent face-to-face module (HAR6045). This is a distance learning version of the face-to-face HAR6045 module.

Please note that some prior understanding of statistics is necessary to study this module. PGT students must previously have taken HAR6035, HAR6039, HAR6042 or an equivalent introductory-level statistics module. PGR students must either have taken one of these modules or had an introductory course in statistics as part of previous studies.


Objectives

This unit aims to:

  1. Introduce students to fundamental concepts and analysis methods in statistics used by health science researchers
  2. Enable students to apply these concepts to critically appraise research literature
  3. Equip students with the knowledge and skills necessary to analyse appropriately 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:

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

These outcomes relate to the following QAA subject-specific skills in health studies:

  • the ability to understand, interpret and critically appraise the statistical information presented in the health and health care literature
  • the ability to draw on research and research methodologies to locate, review and evaluate research findings relevant to health and health issues, across a range of disciplines


Teaching methods

Recorded lectures will be used to impart knowledge of key statistical concepts and methods (Aim 1 and LO 1-7 and 9), while structured exercises using SPSS will apply these concepts to provided example data sets (Aims 2 and 3 and LO 8).

Weekly discussion board hours (including some synchronous webinar sessions) will allow students direct contact with the module leader for questions and discussions.

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: 8 October 2021


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