# Modules

### MCR8019 : Clinical Research Statistics (E-learning)

• Offered for Year: 2020/21
• Module Leader(s): Mr David McGeeney
• Lecturer: Mr Matt Linsley
• Owning School: FMS Graduate School
• Teaching Location: Off Campus
##### Semesters
 Semester 1 Credit Value: 5 Semester 2 Credit Value: 15 ECTS Credits: 10.0

#### Aims

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

#### Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

##### 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 StudyOnline Discussion101:0010:00N/A
Total200:00
##### 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.

#### Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

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

##### Exams
Description Length Semester When Set Percentage Comment
PC Examination202M20Timed Online MCQs, 10 questions
##### Other Assessment
Description Semester When Set Percentage Comment
Essay2M80Critique of Research Extracts (Short answer questions).
##### 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 MCQ is 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.