Module Catalogue 2022/23

MCR8019 : Clinical Research Statistics (E-learning)

  • Offered for Year: 2022/23
  • Module Leader(s): Mr David McGeeney
  • Lecturer: Mr Matt Linsley
  • Owning School: FMS Graduate School
  • Teaching Location: Off Campus
Semester 1 Credit Value: 5
Semester 2 Credit Value: 15
ECTS Credits: 10.0
Pre Requisites
Pre Requisite Comment

A basic understanding of statistical methods is desirable prior to attendance on this programme.

Co Requisites
Co Requisite Comment



This is an on-line course which introduces the statistical packages of MINITAB and SPSS to help students performing clinical research develop an understanding of elementary statistical methods such as estimation and hypothesis testing. It is designed to inculcate a somewhat deeper understanding than usual introductory courses in statistics and so is appropriate for a Masters (FHEQ level 7) course. The module aims to:

1. Inform students about some of the statistical techniques used in collecting data in clinical research.
2. Develop a critical understanding of the statistical methods in analyzing data.
3. Provide students with an understanding about the statistical packages available for analyzing data.

Outline Of Syllabus

The syllabus comprises the following elements:

• An overview of statistical packages particularly SPSS and Minitab
• Statistics - an overview
• Descriptive statistics
• Inferential statistics
• Population and parameters
• Normal distributions
• Samples, estimation and standard errors
• Confidence intervals
• The idea of a hypothesis test
• Tests to compare two groups I: the t-test
• Tests to compare two groups II: binary data
• Principle of sample size calculations
• Survival analysis

Learning Outcomes

Intended Knowledge Outcomes

On completion of the module students will be able to:

• identify appropriate statistical software for analysis of data from studies
• present clinical research data in the most appropriate form
• discuss data post-analysis demonstrating a systematic understanding of the key concepts involved and the meaning of the statistical outcomes

Intended Skill Outcomes

On completion of the module students will be able to:

• apply appropriate statistical software for analysis of data from clinical studies
• perform power calculations where necesary to determine appropriate sample size
• critically appraise the techniques available and the limitations of various techniques in
answering the scientific questions posed
• critically appraise the statistical contribution to published scientific papers

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion230:0060:00N/A
Guided Independent StudyDirected research and reading106:0060:00Online content
Guided Independent StudySkills practice102:0020:00N/A
Guided Independent StudyIndependent study105:0050:00Supplemental reading
Guided Independent StudyOnline Discussion101:0010:00N/A
Teaching Rationale And Relationship

This module will be taught via e-learning using the Blackboard VLE. The design of the material will not only focus on a range of inferential and descriptive statistics, but will also enhance the student's practical ability to apply statistical rigour to clinical research. Teaching will take the form of online tutorials and students will also be able to utilise reflective learning activities such as online discussion boards.

Reading Lists

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Essay2M80Critique of Research Extracts (Short answer questions).
Computer assessment2M202 timed online MCQs (10 questions each)
Formative Assessments
Description Semester When Set Comment
Computer assessment2M3 online MCQs on completed topics
Assessment Rationale And Relationship

The critique is designed to assess how well candidates understand statistical principles as applied to published work and help them develop skills for research and for Masters students to prepare for the dissertation component of the course (later). The MCQs are designed to test the students understanding and knowledge of statistics and the software as taught in the module.

The formative assessment via MCQs tests the students understanding and knowledge of statistics.


Past Exam Papers

General Notes


Disclaimer: The information contained within the Module Catalogue relates to the 2022/23 academic year. In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described. Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2023/24 entry will be published here in early-April 2023. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.