# Modules

### BIO2020 : Experimental Design and Statistics for Biologists

• Offered for Year: 2018/19
• Module Leader(s): Dr Emmi Hall
• Lecturer: Dr Peter Avery
• 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. Reports for assessment are worked examples in minitab which test both statistical understanding and enable the students to learn to use minitab.

#### Outline Of Syllabus

10 x 1hr lectures covering key points to be developed, practised and assessed through the practical sessions

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

##### Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion100:305:00Revision for final exam
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Includes 2hr revision session with key course text book.
Guided Independent StudyAssessment preparation and completion61:006:00Revision of practical classes
Guided Independent StudyAssessment preparation and completion11:301:30Final exam
Scheduled Learning And Teaching ActivitiesPractical61:309:00Includes PC practice and diagnostic tests.
Guided Independent StudyIndependent study102:0020:00Homework exercises (Blackboard on line)
Guided Independent StudyIndependent study118:3018:30Study of lectures, practicals, ReCap, Blackboard etc.
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.
Cluster sessions are designed to develop skills in data manipulation, graphical display, statistical analysis, data interpretation and use of minitab.

#### Assessment Methods

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

##### Exams
Description Length Semester When Set Percentage Comment
PC Examination1201A75Problem solving and data interpretation
##### Other Assessment
Description Semester When Set Percentage Comment
Prob solv exercises1M25Practical assessments (5 x 5%)
##### Formative Assessments
Description Semester When Set Comment
Computer assessment1MHomework exercises (Blackboard)
##### Assessment Rationale And Relationship

The examination and practical tests examine student understanding of statistical knowledge, experimental design and use of minitab. The tests also require students to think in a logical manner.

The formative assessment supports the lectures and the practical tests and will give further practice in use of Minitab for a range of pertinent tasks.

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.