Module Database Search


Module Title
Data Handling Skills In Science

Keywords
Manipulation of formulae, experimental error, best fit, simple probability and statistics

ReferenceAS1009
SCQF LevelSCQF 7
SCQF Points15
ECTS Points7.5
CreatedJanuary 2004
ApprovedSeptember 2004
Amended
Version No.1

Prerequisites for Module

None in addition to Course Entry Requirements.

Corequisite Modules

None.

Precluded Modules

None.

Aims of Module

To provide students with numeracy skills, commensurate with the needs of the modern scientist.

Learning Outcomes for Module

On completion of this module, students are expected to be able to:

1. Manipulate formulae to solve linear, quadratic, exponential and logarithmic equations.
2. Recognise the importance of identifying possible sources of error in scientific measurement.
3. Apply graphical techniques to linear functions and use experimental sets of data points in order to deduce functional relationships.
4. Use simple statistical techniques including graphical representation of data, to produce sample statistics, probability rules and probability distributions in applied problems.

Indicative Module Content

Simple algebra of linear and quadratic functions. Solution of linear and quadratic equations in one variable. Rules of indices and logarithms. Transposition of formulae. Measurement error, accuracy and precision, bias.

Determination of laws using graphs. Equation of the straight line. Regression and the line of best fit. Rates of change. Presentation of data and simple descriptive statistics: measures of location and dispersion. Laws of probability. Normal distributions. Use of Excel in applications to scientific problems.


Indicative Student Workload

Contact Hours

Full Time
Lectures
22
Tutorials
22
Assessments
10

Directed Study

 

26

Private Study

 

70

Mode of Delivery

The course is lecture-based, supplemented by tutorials and laboratories using a computer statistics package such as Excel.

Assessment Plan

Learning Outcomes Assessed
Coursework 1,2,3,4

Assessments will consist of a variety of contextualised problem-based numerical exercises.

Indicative Bibliography

1.REED, R., HOLMES, D., WEYERS, J. AND JONES, A., 2003. Practical Skills in Biomolecular Sciences 2nd ed. Prentice Hall. OR
2.Langford,A.,DEAN, J., JONES, A.M., HOLMES, D., REED, R., WEYERS, J. ,2005. Practical Skills in Forensic Science. Pearson/Prentice Hall .
3.ENNOS, R., 2000. Statistical and Data Handling Skills in Biology. Prentice Hall.
4.HARRIS, M., TAYLOR, G. AND TAYLOR, J., 2005. Catch up Maths & Stats: For the life and medical sciences. Scion Publishing Ltd.

Additional Notes

This module covers, at least in part, the following Health Professions Council Standards of Proficiency for Biomedical Scientists (035/SOP/BMS/A5 July 2004): 3a.1


Robert Gordon University, Garthdee House, Aberdeen, AB10 7QB, Scotland, UK: a Scottish charity, registration No. SC013781