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2019/20 Undergraduate Module Catalogue

BLGY2192 Experimental Design and Analysis

10 creditsClass Size: 200

Module manager: Dr Leslie Firbank

Taught: Semester 1 View Timetable

Year running 2019/20

This module is not approved as a discovery module


Students should be able to design good experiments for field and laboratory use and use SPSS to use a wide variety of statistical techniques for the analysis and presentation of complex multifactorial datasets.

Learning outcomes
On completion of the module students will be able to:
- Demonstrate a broad understanding of the concepts behind the collection, management, analysis and interpretation of numerical data;
- Design an appropriate experiment or survey to collect numercial data;
- Understand the idea of testing hypotheses using the probabilities of the hypotheses being incorrect;
- Analyse and interpret numerical data using techniques including exploratory data analysis; correlation; regression; chi-square; analysis of variance; analysis of covariance, multivariate analysis and other statistical techniques;
- Present data analysis and interpretation in the context of scientific reports.

Skills outcomes
- Team working
- problem solving
- data analysis and interpretation
- scientific reporting
- quality assurance


The course will consolidate existing techniques of level 1, including the use of simple non-parametric statistics such as Mann-Whitney, Wilcoxon's test and Spearman Rank. This will be extended to data management, Two-factor ANOVA with interaction terms, ANCOVA, Box and Whisker plots and other visualisations, alternative data transformations, simple multivariate analysis, and experimental design.

This will be taught within the context of experimental conduct, data interpretation and scientific reporting.

Students will be introduced to new developments in informatics.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours79.50
Total Contact hours20.50
Total hours (100hr per 10 credits)100.00

Private study

- 40 hours: working on exercises in own time (5 x 8 hours)
- 39.5 hours: revision and background reading.

Opportunities for Formative Feedback

Computer based report: individual reports on data analysis problem introduced in week 3, all information presented in week 6. Students can work together to undertake statistical analysis, but the actual reports are individual. Feedback via VLE.

Methods of assessment

Assessment typeNotes% of formal assessment
Reportcomputer based report to undertake statistical analysis and individual write-up20.00
In-course MCQ4 x in-course on-line MCQs covering materials from practical sessions. Each worth 4%.16.00
Total percentage (Assessment Coursework)36.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 00 mins64.00
Total percentage (Assessment Exams)64.00

Past exam papers can be found on-line at the Examinations section of Student Services.

Reading list

The reading list is available from the Library website

Last updated: 25/04/2019


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