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Module

BIO2020 : Experimental Design and Statistics

  • Offered for Year: 2020/21
  • 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 both Minitab and R.

Outline Of Syllabus

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

Observational and experimental design – initial observations, developing hypotheses and predictions, data collection in space and time, replication, independence.
Introduction to statistical analysis
Using figures to visualise and summarise data; Probability; Probability distributions (Normal and Binomial).
Introduction to statistical inference; measures of precision; degrees of freedom.
Tests for differences between two samples; t-tests (paired and unpaired); sample size calculations.
Non-parametric tests: Mann-Whitney test; Goodness of fit tests for frequency data (Chi squared); Poisson distribution; two-way tables - tests for independence.
Tests for differences between multiple samples: ANOVA (1-way and 2-way); post-hoc analysis to compare means; Kruskal-Wallis test; testing for interactions.
Relationships between variables; Correlation (Pearson and Spearman's rank); Fitting a straight line (regression).
Further regression methods: model checking; quadratic regression; multiple regression.
Review: matching statistical analyses to hypotheses and data.
(Lectures 1 & 2 by Biology staff, Lectures 3-10 by Maths staff)

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

Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials101:0010:00online lecture materials
Guided Independent StudyAssessment preparation and completion125:0025:00Main assessment
Guided Independent StudyAssessment preparation and completion15:005:00Short assessments online
Guided Independent StudySkills practice82:0016:00Data analysis practice
Guided Independent StudySkills practice201:0020:00Guided online tutorials hosted on R shiny
Structured Guided LearningStructured non-synchronous discussion61:006:00Online webinars to demonstrate techniques and help students with practicals (RAS, ACM)
Guided Independent StudyIndependent study117:0017:00Independent study
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 Minitab and R studio.

Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

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

Other Assessment
Description Semester When Set Percentage Comment
Computer assessment1M255 x computer tests (5 % each)
Computer assessment1M75Synoptic computer test
Assessment Rationale And Relationship

The computer assessments weighted 5% each allow students to continuously assess their learning and they are provided with regular feedback from these short tests. The final 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