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The University of Southampton

MEDI6232 Research Skills for Biomedical Science 1 (RSBS 1)

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

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Understand the nature and value of a research hypothesis and what hypothesis testing is (Programme LO A4, B1, B2, B5 and D2)
  • Understand how important a research hypothesis is for the development of a research proposal (Programme LO A4, B1, B2, B5 and D2)
  • Understand the value, nature, uses and limitations of a range of research methods (Programme LO A2)
  • Identify and justify the value of different sources of data in drawing conclusions from published literature (Programme LO A4)
  • Understand how to use a variety of statistical techniques(Programme LO C3)
  • Understand the differences between various statistical techniques (Programme LO C3)
  • Know how to use SPSS and GraphPad Prism software to manage, present and analyse data (Programme LO C4)
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)
  • Distinguish between appropriate and inappropriate use of statistical techniques (Programme LO B1, B2 and B5)
  • Identify and perform appropriate data presentation and summary (Programme LO C3, C4 and D2)
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • 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)
  • Direct your own learning (Programme LO C1, C2, C3 and C4)
  • Exercise initiative and personal responsibility (Programme LO C1, C2, C3 and C4)
Cognitive Skills

Having successfully completed this module you will be able to:

  • Differentiate the value of information from different types of study designs and different sources (Programme LO A4 and B1)
  • Critically assess research carried out by others, evaluate its usefulness for your own practice (Programme LO A2, A4 and D2)
  • Differentiate between the different types of data (Programme LO A4, B1 and B5)
  • Identify appropriate statistical techniques for data analysis (Programme LO A2, A4.B1, B2, B4 and B5)
  • Apply knowledge of effective communication skills in written format (Programme LO A2, A3, B1, B2, B5, C4 and D2)


• 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.

Independent Study65
Total study time100

Resources & Reading list

Altman D.G., Machin D., Bryant T.N. & Gardner M.J (2000). Statistics with Confidence. 

Confidence Interval Analysis.

Power and Sample Size Calculation.

Electronic Statistics Textbook.

Statistics for the Terrified.

Bland M. (2000). An Introduction to Medical Statistics. 

Altman D.G. (1991). Practical Statistics for Medical Research. 

Kirkwood B.R. & Sterne J.A.C. (2003). Essential Medical Statistics. 

Machin D. and Campbell M.J. (2005). The Design of Studies for Medical Research. 

Bowling, A. (2001). Research Methods in Health: Investigating Health and Health Services. 

UCLA Statistical Computing Resources.

GraphPad PRISM.

Faculty of Medicine web site.

Field A. (2009). Discovering Statistics Using SPSS for Windows.. 

SPSS downloaded.

Campbell M.J., Machin D. & Walters S.J. (2007). Medical Statistics: A Textbook for the Health Sciences. 


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.


Class discussions


MethodPercentage contribution
Assignment 100%


MethodPercentage contribution
Assignment 100%


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

Resources for the module will be available on Blackboard. Required software will be available to students from University workstations or through iSolutions.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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