Exploring data sets with and without using software.
Types of data, nominal, ordinal, quantitative, discrete, continuous
Graphical representation of data (e.g. bar charts, scatter graphs, boxplots, histograms)
Use of statistical methods (e.g. mean, standard deviation, correlation) and analysis for a wide range of statistical data sets
Writing statistical reports
Use of statistics in quality control
Development of transferable skills in teamworking and communication and presentation skills including creating a poster using presentation software such as Powerpoint.
Probability rules and Bayes' Theorem
Probability problems using standard statistical distributions such as Binomial, Poisson, Normal and Exponential.
Modelling univariate and bivariate discrete random variables using appropriate probability distributions.
Hypothesis testing including goodness of fit tests.

Students are required to commit to 300 learning hours of which 78 hours will consist of contact time via 24 lectures (1 per week) and 48 hours (2 per week) of tutorial/practicals and 6 hours of dedicated lab based skills sessions. Lectures will provide students with a broad overview of the indicative content and the tutorial/practical sessions will allow students to practise the material covered in the lectures through problem solving.
Students will investigate these datasets in the practical sessions to bring out the main features of the data. Students will work both individually and in groups and will communicate their results both orally and in writing.

The coursework consists of a report weighted at 25% based on a quality control scenario assessing Learning Outcomes 1 & 2 and a group presentation weighted at 25% involving the collection, presentation including a poster, analysis of data and communication of results assessing Learning Outcomes 1 & 2.

The class test comprises 2 one hour class tests each weighted at 25% assessing Learning Outcomes 1, 3 & 4.

The class test is the final assessment point.

For background reading only, e.g.
Business Data Analysis using EXCEL, D. Whigham, OUP 2007, ISBN: 019929628-6
Quantitative Data Analysis Using SPSS, Pete Greasley, OUP 2008, ISBN: 0335223052
SPSS Survival Manual, Julie Pallant, OUP 2010, ISBN: 9780335242399
Introduction to Probability, Grinstead & Snell, AMS 1997, ISBN: 0821807498
Probability Models, Sheldon M. Ross, Academic Press 2003, ISBN: 0125980612

SPSS

None