Module overview
This module will introduce you to key concepts underlying a broad range of biomedical research methodology. The module will focus on developing your understanding of what a research hypothesis is and what hypothesis testing is, how it is structured with aims and learning outcomes, how you construct a research hypothesis yourself and develop it into a research proposal. The module will also develop your understanding of various appropriate statistical methodologies including data distribution, confidence intervals, significance testing, data manipulation, parametric and non-parametric tests, sample size and power calculations, correlation and regression, ANOVA and multiplicity. During the module you will also study methods of organising data sets and consider how to present data and statistical findings appropriately. The course is taught through a combination of lectures and interactive sessions using computer workstations. Practical examples of datasets derived from research groups within the Faculty will be used to provide context to the theoretical aspects of the course. You will be taught how to use both SPSS and Graphpad PRISM for both statistical analysis and presentation of data. At the end of this module, you should understand how to analyse a variety of types of data, and to be able to evaluate the analysis of data in published research.
Aims and Objectives
Learning Outcomes
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Direct your own learning (Programme LO C1, C2, C3 and C4)
- Use Information Technology to analyse and present research findings (Programme LO C3 and C4)
- Organise your own activities to achieve a desired outcome within a limited amount of time (Programme LO C1, C2, C3 and C4)
- Exercise initiative and personal responsibility (Programme LO C1, C2, C3 and C4)
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Understand how to use a variety of statistical techniques(Programme LO C3)
- Understand the nature and value of a research hypothesis and what hypothesis testing is (Programme LO A4, B1, B2, B5 and D2)
- Understand the differences between various statistical techniques (Programme LO C3)
- Identify and justify the value of different sources of data in drawing conclusions from published literature (Programme LO A4)
- Understand how important a research hypothesis is for the development of a research proposal (Programme LO A4, B1, B2, B5 and D2)
- Know how to use SPSS and GraphPad Prism software to manage, present and analyse data (Programme LO C4)
- Understand the value, nature, uses and limitations of a range of research methods (Programme LO A2)
Cognitive Skills
Having successfully completed this module you will be able to:
- Critically assess research carried out by others, evaluate its usefulness for your own practice (Programme LO A2, A4 and D2)
- Apply knowledge of effective communication skills in written format (Programme LO A2, A3, B1, B2, B5, C4 and D2)
- Differentiate the value of information from different types of study designs and different sources (Programme LO A4 and B1)
- Identify appropriate statistical techniques for data analysis (Programme LO A2, A4.B1, B2, B4 and B5)
- Differentiate between the different types of data (Programme LO A4, B1 and B5)
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Identify the appropriate use of quantitative methods (Programme LO A2, B1, B2, B4 and B5)
- Identify and perform appropriate data presentation and summary (Programme LO C3, C4 and D2)
- Distinguish between appropriate and inappropriate use of statistical techniques (Programme LO B1, B2 and B5)
Syllabus
• Types of Research
• Developing a Research Hypothesis and Proposal
• Chance, Bias and Confounding
• Accuracy, Reliability and Validity
• Types of Data
• Statistical Concepts and Techniques
• Hypothesis Testing
• Regression analysis
• Sample size calculation
• Data Manipulation
• Use of SPSS and PRISM
Learning and Teaching
Teaching and learning methods
A variety of methods will be used including lectures, active participatory methods, e-learning/interactive tools for learning and self-assessment, computer demonstrations and practical exercises using computers, guided reading, group study and individual study
Lectures recorded on Panopto, online live support sessions on MS Teams will also be held.
| Type | Hours |
|---|---|
| Independent Study | 65 |
| Teaching | 35 |
| Total study time | 100 |
Resources & Reading list
Internet Resources
UCLA Statistical Computing Resources.
Power and Sample Size Calculation.
Textbooks
Campbell M.J., Machin D. & Walters S.J. (2007). Medical Statistics: A Textbook for the Health Sciences.
Kirkwood B.R. & Sterne J.A.C. (2003). Essential Medical Statistics. Oxford: Blackwell Science Ltd.
Altman D.G. (1991). Practical Statistics for Medical Research. Chapman and Hall.
Altman D.G., Machin D., Bryant T.N. & Gardner M.J (2000). Statistics with Confidence. BMJ Books.
Bowling, A. (2001). Research Methods in Health: Investigating Health and Health Services. Milton Keynes: Open University Press.
Machin D. and Campbell M.J. (2005). The Design of Studies for Medical Research. John Wiley and Sons.
Bland M. (2000). An Introduction to Medical Statistics. Oxford: Oxford Medical Publications.
Field A. (2009). Discovering Statistics Using SPSS for Windows.. London: Sage Publications.
Assessment
Assessment strategy
The assessment for the module provides you with the opportunity to demonstrate achievement of the learning outcomes. There will be one assessment: - a report of the analysis of a set of data appropriate to the student’s discipline Assessment 1: Analysis of a set of data appropriate to the your discipline (100%) You will demonstrate that you can: • Analyse a set of data using SPSS and GraphPad PRISM • Modify and transform the data to create derived data • Summarise the data in tabular or graphical form to publication quality • Make comparison between groups using appropriate statistical techniques • Report analyses to publication standard Assessment requirements You must pass the module overall at 50% or above. The assessment must be passed. Candidates who fail the module at the first attempt will be permitted to re-sit a supplementary assessment as agreed by the module lead. Candidates who achieve at least 50% overall at the second attempt will be permitted to pass the module and the module mark will be capped at 50%. Method of repeat year: There is no opportunity to repeat the year for students enrolled on the iPhD programme. For students enrolled on the MRes in Stem Cells, Development & Regenerative Medicine it is only possible to repeat internally.Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Class discussions
- Assessment Type: Formative
- Feedback: Verbal feedback from facilitators and peer-group
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Assignment | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Assignment | 100% |