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Module

BIO2020 : Experimental Design and Statistics

  • Offered for Year: 2021/22
  • Module Leader(s): Dr Roy Sanderson
  • Lecturer: Professor Stephen Rushton, Dr Cristiano Villa, Dr Aileen Mill
  • Owning School: Natural and Environmental Sciences
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

To introduce and practise the development of hypotheses, appropriate experimental design, robust data manipulation and analysis, appropriate statistical testing and interpretation.
This module is a combination of taught material and linked practical exercises aimed at developing the problem-solving and statistical skills required by research biologists. It will introduce the concepts of hypothesis driven research, proper experimental design, data manipulation and statistical testing. It will improve the confidence of biology students in dealing with the analysis and interpretation of numerical data. Students will learn analyses using R and interactive websites.

Outline Of Syllabus

Lectures covering key points to be developed, practised and assessed through the practical sessions

Understanding different types of data, response and explanatory variables.
How to visualise and summarise data.
Good practice in experimental design
Linear models as a general approach to analysing univariate data
Generalised linear models to analyse data with non-normal distributions

Further regression methods: model checking; quadratic regression; multiple regression.
Review: matching statistical analyses to hypotheses and data.
(2 lectures by SNES staff and 8 by Maths staff)

Practicals for PC cluster-based activities: a variety of examples from different areas of biology will be used.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture91:009:00Lectures
Guided Independent StudyAssessment preparation and completion15:005:00Online quizzes on interactive websites
Guided Independent StudyAssessment preparation and completion125:0025:00Main assessment
Scheduled Learning And Teaching ActivitiesPractical62:0012:00Practicals
Structured Guided LearningAcademic skills activities122:0024:00Online interactive websites/asynchronous teaching
Guided Independent StudySkills practice201:0020:00Guided online tutorials hosted on R shiny
Structured Guided LearningStructured non-synchronous discussion41:004:00Online webinars to demonstrate techniques and help students with practicals (RAS, ACM)
Scheduled Learning And Teaching ActivitiesModule talk11:001:00Introductory / orientation lecture to get students familiar with format and delivery of module (RAS)
Total100:00
Teaching Rationale And Relationship

Lectures will introduce students to the key stages in scientific investigation including a) clearly defined hypotheses; b) robust experimental design; c) data interpretation; and d) appropriate use of statistical tests.
Computer practicals are designed to develop skills in data manipulation, graphical display, statistical analysis, data interpretation and use of R studio.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Computer assessment1M100Synoptic computer test via Canvas
Formative Assessments
Description Semester When Set Comment
Computer assessment1Mvia Canvas
Assessment Rationale And Relationship

The computer assessment examines students' understanding of experimental design and statistics and ability to think in a logical manner, including identifying and applying appropriate analyses.

Study Abroad students may request to take their exam before the semester 1 exam period, in which case the format of the paper may differ from that shown in the MOF. Study Abroad students should contact the school to discuss this.

Reading Lists

Timetable