# Module Information

Module Identifier
BRM3200
Module Title
Statistics for Experimental Scientists
Academic Year
2013/2014
Co-ordinator
Semester
Semester 1 (Taught over 2 semesters)
Other Staff

#### Course Delivery

Delivery Type Delivery length / details
Lecture 1 x 2 hour introductory lecture
Seminars / Tutorials 5 x 2 hour practical workshops

#### Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment 3 Hours   On-line Assessment No 1.  10%
Semester Assessment 3 Hours   On-line Assessment No 2.  10%
Semester Assessment 3 Hours   On-line Assessment No 3.  10%
Semester Assessment 3 Hours   On-line Assessment No 4.  10%
Semester Assessment 3 Hours   On-line Assessment No 5.  10%
Semester Assessment 3 Hours   On-line Assessment No 6.  10%
Semester Assessment 3 Hours   On-line Assessment No 7.  10%
Semester Assessment 3 Hours   On-line Assessment No 8.  10%
Semester Assessment 3 Hours   On-line Assessment No 9.  10%
Semester Assessment 3 Hours   On-line Assessment No 10.  10%
Supplementary Assessment Students must take elements of assessment equivalent to those that led to failure of the module.  100%

### Learning Outcomes

On completion of this module students will be able to:

1. Identify appropriate methods of analysis for different types of data.

2. Analyse data using a range of statistical analyses.

3. Interpret the results of data analyses.

4. Apply statistical knowledge in the context of postgraduate reserch.

### Content

The module will consist of ten, self contained sub-units each comprised of: Panopto video(s) describing and demonstrating the technique, formative exercises and summative assessment.

All students will undertake a core of four sub-units reinforcing basic statistical procedures: T-tests, ANOVA, Correlation/Regression and Non-parametric tests.

Degree schemes will choose a further six sub-units from the following subject areas:

Data handling and presentation
Multifactorial ANOVA
Post-hoc significance tests
Repeated measures/Split plot ANOVA
Cross over designs
Multivariate Analysis of Variance (MANOVA)
Principle Component Analysis
Multiple Regression
Curvilinear Regression
Canonical Variate Analysis (CVA)
Discriminant Function Analysis (DFA)
Survey/questionnaire design and analysis
GIS

### Module Skills

Skills Type Skills details
Application of Number Most aspects of the module will require manipulation of data and application of statistics.
Communication The ability to present results of scientific research and their statistical analysis in a clear and concise manner will be developed
Improving own Learning and Performance Students need to be capable of organising themselves to ensure that sub-units are completed at the appropriate rate.
Information Technology Students will be expected to use statistical packages to manipulate and analyse data.
Problem solving Students are required to develop a means of collecting data to answer a specific research question
Research skills Students will develop the skills required to interpret and evaluate data presented in scientific literature.

### Notes

This module is at CQFW Level 7