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FB1EM1-Mathematics and Computing for Life Sciences

Module Provider: Food and Nutritional Sciences, School of Chem, Food and Nutr Sci, and Pharm
Number of credits: 20 [10ECTS credits]
Level: 4
Terms in which taught: Autumn and Spring
Module Convenor: Dr RA Frazier
Pre-requisites:
Co-requisites:
Modules excluded:
Module version for: 2009/0

Email: r.a.frazier@reading.ac.uk

Aims:
The aim of this module is to familiarise students with the language of Mathematics and introduce them to the basic use of speadsheet software. It is particularly designed to help students without A/AS level Maths recover numerical skills which they may have lost. The learning event is intended to enable the students acquire basic mathematical and computing skills necessary to learn other laboratory and taught science-based skills.

Assessable learning outcomes:
On completion of the module, students should be able to:

  • operate normal scientific calculators;
  • use basic operations in a standard spreadsheet software;
  • perform basic mathematical calculations using elementary algebra, graphs and calculus;
  • use the SI system of units and undertake conversion between SI and other practical systems of units.
  • Interpret scientific data using appropriate statistical tools to test correlation and scientific hypotheses.

    Additional outcomes:
    The students will acquire a knowledge of the quantitative methods used in scientific analysis, and acquire the necessary analytical and numerical skills. Fluency in the use of computers.

    Outline content:
    Real number system. Use of calculator functions. Units and conversions. Topics in basic algebra. Elements of co-ordinate geometry, straight lines and other graphs. Laws of indices. Logarithms. Simultaneous and quadratic equations. Differential calculus (differentiation of functions using formulae), application of differentiation as a rate measure, maxima and minima, partial differentiation. Integration, interpretation of integration limits, definite integrals. Elementary statistics, averages, probability distributions, hypothesis testing, data correlation, linear regression. Introduction to spread sheets, manipulating data sets using spreadsheets, plotting graphs, correlating data and interpreting relevant statistics.

    Brief description of teaching and learning methods:
    Lectures, workshop tutorials and the use of standard computer software, all supported by Blackboard.

    Contact hours:

      Autumn Spring Summer
    Lectures 10 10
    Tutorials/seminars 38  10  12 
    Practicals    
    Other contact (eg study visits)      
    Total hours 48  23  12 
    Number of essays or assignments  
    Other (eg major seminar paper)      

    Assessment:
    Coursework
    Coursework assignments will include 2 assessed problem sheets and a practical exercise based on the use of spreadsheet software. Each assignment will carry 10% marks.
    Relative percentage of coursework :30%
    Penalties for late submission
    In accordance with University Policy on Late Submission of Coursework
    Examinations
    Written examination during the Summer Term
    Requirements for a pass
    40% overall in all assessed work
    Reassessment arrangements
    Written examination during the University re-examination period (late August / early September)

    Last updated: 23 November 2009

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