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Unit information: Statistics and R in 2020/21

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Statistics and R
Unit code BIOLM0029
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Clements
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department School of Biological Sciences
Faculty Faculty of Life Sciences

Description

This unit will introduce students to the theoretical and practical aspects of statistical approaches to analysing biological data. These include the design of statistical tests and use of tools such the R programming language. The students will have opportunity to plan, develop and implement their own statistical analyses to answer a wide variety of biological questions.

The aim of this unit will be to:

  1. Provide students with a detailed understanding of the concepts behind designing and performing statistical analyses.
  2. Provide students with the skills required to use and interact with the R software environment to perform their analyses.

Intended learning outcomes

The Learning Outcomes (LOs) for this unit are:

A: Knowledge and Understanding:

  1. to understand the theoretical aspects and rationale behind the choice and use of statistical analyses.
  2. to develop knowledge on the different data structures used in R and how these data can be manipulated
  3. to acquire the concepts behind the use of libraries in R, data visualisation and presentation.

B: Intellectual Skills/Attributes:

  1. to devise the best statistical design to analyse different biological data.
  2. to design R scripts and critically assess their suitability to different analysis types.
  3. to plan the best use of different resources (modules, libraries, etc.) to solve different statistical analyses.

C: Other Skills /Attributes (Practical/Professional/Transferable):

  1. to acquire proficiency performing statistical tests using R.
  2. to demonstrate competence with R to write scripts and data visualisation techniques.
  3. To gain strengths in computer coding, code sharing, and open source programming

Teaching details

The unit will be delivered through a mixture of short lectures followed by individual exercises with computers. Blackboard will be used to engage students with the unit content.

Assessment Details

A summative computer assessment will consist of a final computer task integrating all the learning objectives.

Reading and References

Beckerman, Childs, Petchey. Getting started with R. Oxford press

Wickham & Grolemund. R for data science. O’Reilly.

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