Course Details in 2026/27 Session

Module Title	LH Experimental Data Interpretation
School	Institute of Clinical Sciences
Department	Institute of Clinical Sciences
Module Code	02 34041
Module Lead	Dr Laura O’Neill
Level	Honours Level
Credits	10
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	It is a requirement that students achieve a mark of at least 35% in their summative exam
Exclusions
Description	The module will consolidate your research skills acquired across the Programme and focus on your ability to critically evaluate research data to determine 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 focus on consolidating your understanding of quantitative data analysis using various appropriate statistical methodologies (e.g.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 appreciate the ethical and regulatory requirements aligned to the data set and be required to organise the data sets and consider how to tabulate and present the data showing any statistical findings appropriately. Practical examples of datasets derived from research groups will be used to provide context to the theoretical aspects of the research area. You will be use appropriate mathematical programmes (e.g. SPSS,Graphpad PRISM, Excel) for both statistical analysis and presentation of data. At the end of this module, you should demonstrate your ability to analyse a variety of types of data, and to be able to evaluate the analysis of data in published research.
Learning Outcomes	By the end of the module, students should be able to: Understand the regulatory and ethical acquisition, methods, concepts and theoretical principles, which underpin quantitative data gathering and analysis Demonstrate implementation of statistical techniques and tools and appropriately apply them to different segments and types of quantitative data Use computer programs to manipulate available datasets demonstrating different levels of analysis from descriptive to multivariate analysis
Assessment	34041-01 : Overall module mark : Coursework (100%)
Assessment Methods & Exceptions	Assessments: The module is assessed by In course assessment (100%) Analysis of a set of data appropriate to a biomedical research discipline and production of a report of the analysis Reassessment: Academic failure: If a student fails the module then they will be required to revise and resubmit the assessment. Failure to submit: Submission of coursework is compulsory for the programme. Students will be required to submit outstanding work to meet the module outcomes.
Other
Reading List