Module Information

Module Identifier
BRM5500
Module Title
Research methodology and advances in Biosciences
Academic Year
2016/2017
Co-ordinator
Semester
Semester 1 (Taught over 2 semesters)
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 20 x 1 Hour Lectures
Miscellaneous 1 x 1 Hour Miscellaneous
Miscellaneous 7 x 9 Hour Miscellaneous
Seminar 6 x 1 Hour Seminars
Field Trip 1 x 9 Hour Field Trip
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Summative on line assessments, related to each statistical  on line session (x 10)  50%
Semester Assessment Interpretation of results/solutions applied to practice  (as appropriate to the degree scheme using this module)  35%
Semester Assessment Research proposal  15%
Supplementary Assessment Students must take elements of assessment that are equivalent to those that led to failure of the module.  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Applying statistical knowledge in the context of postgraduate research.

2. Identifying appropriate methods for different types of data.

3. Anaylsing and interpret the results from a range of different statistical analyses.

4. Generating appropriate research hypotheses and research objectives.

5. Assimilating and synthesizing of information from a variety of sources.

6. Clearly communicating research findings.

Brief description

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.

Aims

The module aims to develop investigation skills and provides training relevant to assessments within other modules, including the Masters dissertation.

Content

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.


Module Skills

Skills Type Skills details
Application of Number Students will be taught statistical techniques and expected to complete both formative and summative assessment.
Communication Students will be expected to be able to express themselves appropriately in their assignments.
Improving own Learning and Performance Detailed feedback will be given for assignment work.
Information Technology Students will be required to source information from a variety of scientific publication data bases and be taught to use specialist statistical software.
Personal Development and Career planning Research Project Plan - developed in collaboration with employer and supervisor.
Problem solving Online quizzes will be used to help develop and improve students problem solving skills.
Research skills Students will be required to undergo directed self study and so will develop their literature research skills.
Subject Specific Skills
Team work

Notes

This module is at CQFW Level 7