Module Information

Students undertaking the module will explore a range of basic quantitative statistic techniques suitable for biological data. These will lead on to more complex statistical procedures including multi-factorial ANOVA, multivariate analyses and aspects of experimental design.
Various formats of scientific reporting are also considered including: dissertations, literature reviews, submissions for targeted publications and other media. In addition, the importance of scientific objectivity and the ethical considerations surrounding experimental research will be considered.

This module provides the tools necessary for carrying out independent research. Part 1 will cover quantitative and qualitative statistical methods for analyzing data. Part 2 will build towards the students identifying a suitable dissertation topic and will be taught to evaluate existing research published in a range of different sources. The students will also evaluate the different knowledge exchange mechanisms that are appropriate to the audience.

The aim of this module is to provide training relevant to assessments within other modules, including the Masters dissertation. The module will cover the following principal areas:

Part 1: research skills

• The nature of research and the research process
• Evaluation of quantitative and qualitative research
• Assessment of published research
• Scientific writing and the production of a postgraduate dissertation

Part 1 has two assessments. The first assessment will evaluate the student's ability to review published literature, and synthesize and communicate their findings in a clear and concise manner. The second assessment is a research proposal on their choice of dissertation topic and will detail the hypothesis that will be tested, highlight some of the key research publications in their chosen area and present the experimental design they intend to implement, including detail on the statistical methods they intend to utilize.

Part 2: statistics

• T-tests, ANOVA, post-hoc significance tests, data handling and presentation Correlation/Regression and Non-parametric tests.
• Students will choose a further three sub-units from the following subject areas:
• Multifactorial ANOVA, repeated measures, split plot ANOVA, Multivariate Analysis of Variance (MANOVA), principal component analysis, canonical variate analysis (CVA), discriminant function analysis (DFA), survey/questionnaire design and analysis, introduction to R.

Part 1 will contain a range of sessions which will explore developments in Biosciences research and scientific publication
Part 2 of the module will contain a range of recorded lectures detailing each statistical test and instructive guides on how to perform each statistical test using specialist statistics software. Online formative and summative assessments will test the student's understanding and application of each statistical test.