Statistics and Experimental Design for Bioscientists
Duration 1 day
Training Units 10.0
Team Researcher Academy

Target Audience

Post graduate students, post docs, staff.

 

Process

Lectures and computer practical sessions.

 

Course Description

This module attempts to explain the major principles and techniques of statistical analysis of research data without becoming too involved in the underlying mathematics.  Now that computer software is very well established for data analysis, it is more important to understand WHAT a statistical test is doing (and thus whether or not it is appropriate) than to be able to perform the underlying calculations by hand.  It is equally important to collect data in an appropriate and planned manner for later analysis.

 

At the end of the course, participants should have an overall grasp of the major analytical techniques available, and how they relate to each other, and have developed abilities in experimental design, data analysis using appropriate software and presentation of results.

 

This module serves students taking the MSc courses in Crop Improvement, Sustainable Bioenergy, Plant Genetic Manipulation or Integrative Biology and the MRes in Advanced Genomic & Proteomic Sciences or the MSci in Environmental Science.  Additionally, this module is often taken on a voluntary basis by Post-graduate students, Post-docs and other staff from other Divisions within the School of Biosciences
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