Quantitative methods for Life Sciences
Life Sciences (School of)
Autumn & Spring
Undergraduate: Level 4
Thursday 03 October 2019
Friday 20 March 2020
25 September 2019
Requisites for this module
BSC C700 Biochemistry,
BSC C701 Biochemistry (Including Placement Year),
BSC C703 Biochemistry (Including Year Abroad),
BSC CR00 Biochemistry (Including Foundation Year),
BSC C100 Biological Sciences,
BSC C101 Biological Sciences (Including Year Abroad),
BSC C102 Biological Sciences (Including Placement Year),
BSC CD00 Biological Sciences (Including Foundation Year),
BSC B990 Biomedical Science,
BSC B991 Applied Biomedical Science (NHS placement),
BSC B995 Biomedical Science (Including Year Abroad),
BSC B999 Biomedical Science (Including Placement Year),
BSC BD00 Biomedical Science (Including Foundation Year),
BSC C400 Genetics,
BSC C402 Genetics (Including Year Abroad),
BSC C403 Genetics (Including Placement Year),
BSC CK00 Genetics (Including Foundation Year),
BSC C161 Marine Biology (Including Foundation Year),
BSC C164 Marine Biology,
BSC CC60 Marine Biology (Including Year Abroad),
BSC CC64 Marine Biology (Including Placement Year),
MMB C160 Marine Biology,
BSC C200 Human Biology,
BSC C201 Human Biology (Including Year Abroad),
BSC C202 Human Biology (Including Placement Year)
The aim of this module is to provide all 1st year Bioscience students with the necessary quantitative skills to enhance performance in other first year modules and to prepare you for your second and third year. Students will develop their skills in areas including experimental design, data handling, display and interpretation, basic statistical analysis, and computational data analysis. Teaching and learning will be through a mixture of lectures and practicals.
To pass this module students will need to be able to:
1. demonstrate an understanding of the scientific method, experimental design and investigation in the biosciences;
2. use scientific units and simple algebra and demonstrate understanding of logarithms, exponentials, geometry and elementary calculus;
3. use basic IT systems effectively for data handling and presentation;
4. be able to analyse data from experiments and draw sound conclusions about the underlying processes using their understanding of mathematics and statistics;
5. be able to analyse biological data using the R programming language.
No information available.
No information available.
One MCQ (Multiple Choice Questions) exam in wk 15 contributing 50% to the overall mark.
Coursework(contribution to the overall mark):
1 Maths on-line assessments: 12.5%
1 Statistics worksheet: 12.5%
Data analysis: 25%
Mixture of lectures, classes and tutorials.
This module does not appear to have a published bibliography.
Assessment items, weightings and deadlines
|Coursework / exam
||50 minutes during January (Multiple Choice)
Module supervisor and teaching staff
Excluding tutors, Dr Radu Zabet, Dr Toni Marco, Prof Leo Schalkwyk, Dr Eoin O'Gorman, Dr Emmanuele Conte
School Undergraduate Office, email: bsugoffice (Non essex users should add @essex.ac.uk to create the full email address)
Dr Clive Butler
The University of Exeter
Associate Professor of Microbial Biochemistry
Available via Moodle
Of 30 hours, 24 (80%) hours available to students:
6 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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