Module Overview

Research Methods and Data Analysis

This module will provide a research toolkit for stage four students to enable them to carry out research in the broad field of medical science. It will consolidate good research practices by drawing together research skills gained throughout the academic programme to prepare students for completion of BIOL4907 and BIOL4910 (Research Project). While the focus of the module is on the field of medical science, the principles are applicable to all research endeavours.

Module Code

BIOL 4909

ECTS Credits


*Curricular information is subject to change

The CORU Standards of Proficiency covered, wholly or in part, in this module within the following domains are:

  1. Professional autonomy and accountability: 15,18,19
  2. Communication, collaborative practice and team work: 3,7
  3. Safety and Quality: 17


Professional knowledge and skills: 19, 32-34

Advanced literature handling

Maximising breadth and depth of searches including clinically focused searches (e.g. PICO) and Evidence based data sources (e.g. NICE)Automating searches and connectivity with reference managing platforms (e.g. Mendeley, EndNote)Approaches to synthesis of the literature

Hypothesis development

Critical evaluation of available knowledge/dataIdentification of knowledge gapsFormulation of robust and testable hypothesis

Study Design

Types of research study, including experimental and epidemiological modelsCharacteristics of good research studies (e.g. statistical power and sample size, relevant research standards such as STARD)Data collection requirements (e.g. sample type, types of replicates, patients, biobanking)Ethical, GDPR and HRR requirements (e.g. balancing power imbalances in research, consent and individual agency of research participants)

Good research practice

Maintaining integrity in research practice (e.g. obligations of the researcher under national and international policies, ethical requirements, obligation to notify of breaches)Data management planning and FAIR principlesMaintaining the laboratory notebook/recordPlanning the research (e.g. time management, aims and objectives, project planning, milestones, deliverables, risks and setbacks, stratification of test selection)How to write scientifically (e.g. development of an academic writing plan, syntactic databases, paraphrasing, avoiding plagiarism in specialised areas) for scientific, professional and lay audiences

Data analysis and interpretation

Application of descriptive and inferential statistics to authentic research data, in the context of medical scienceChoosing the correct statistical approach and recognising the underlying assumptions and limitations such approachesInterpretation of the results of statistical analysisAnalytical and diagnostic performance characteristics (e.g. predictive values, ROC analysis)Principles of honest data display for publicationUse of statistical software packages for data analysis (e.g. MedCalc, SPSS, GraphPad, R)

This module will be delivered in a blended format via data interpretation workshops (6h), lectures and workshops (6h) and guided online activities (12h). Students will be expected to engage in 76 hours of self-directed learning using the resources provided as part of the module Face-to-face delivery will ‘bookend’ the module with core material introduced at the start of the module and an opportunity for reflection and consolidation at the end of the module.

Module Content & Assessment
Assessment Breakdown %
Other Assessment(s)100