Introductory description

This module will demonstrate how mathematics is an interdisciplinary subject, with particular attention to the life sciences.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Number skills

• Decimal and standard form
• SI units and conversion
• Exponentials and logs

Statistics: representing data, measures of location and dispersion

• Statistical variables and measurements
• Frequency distribution (including graphs)

Simple probability and probability distributions

• Calculating probability
• Probability distribution (discrete)
• Normal distribution

Population and sample, sampling distribution

• Populations and Samples
• Standard error
• Parametric and non-parametric statistics

Inferential statistics

• Confidence intervals
• Hypothesis testing
• t-tests

Learning outcomes

By the end of the module, students should be able to:

• Accurately use mathematical notation, terminology, conventions and units and interpret in mathematical terms verbal, graphical and tabular information
• Apply a range of statistical methods to real-world problems in order to provide supporting information to draw evidence based conclusions
• Manipulate, analyse and interpret data using computer software in order to justify conclusions

Indicative reading list

Field, A.P. (2018) Discovering statistics using IBM SPSS. Sage Publications., London.

Emden, H. (2019) Statistics for Terrified Biologists. Blackwell Publishing, USA

Aitken, M. and Broadhurst, B and Hladky, S. (2010) Mathematics for Biological Scientists. Garland Science, USA

Howell, D.C. (2017). Fundamental statistics for the behavioral sciences. W. Ross MacDonald School Resource Services Library, Brantford, Ontario.

Interdisciplinary

This module supports other scientific disciplines through the learning of statistical analysis methods and mathematical software which are widely used across these empirical disciplines. Data is sourced and analysed from within the context of these other disciplines.

Subject specific skills

Students will develop a core understanding of key statistical concepts, with a focus on the application of these fundamental principles within other scientific disciplines. Students will develop a familiarity with the language and terminology of mathematics and will be encouraged to think creatively and critically and identify trends and patterns.

Transferable skills

Students will develop their organisational, time management, computing and communication skills. Students will learn to select and manage information drawn from books, experiments, and the internet. Students will learn to make value judgements about their own work and the work of peers.