Module Descriptors
INTRODUCTORY STATISTICS AND PROBABILITY
MATH40296
Key Facts
Faculty of Computing, Engineering and Sciences
Level 4
30 credits
Hours of Study
Scheduled Learning and Teaching Activities: 72
Independent Study Hours: 228
Total Learning Hours: 300
Assessment
- COURSEWORK weighted at 50%
- COURSEWORK weighted at 50%
Module Details
Module Learning Strategies
Students are required to commit to 300 learning hours of which 72 hours will consist of contact time via 24 lectures (1 per week) and 48 hours (2 per week) of tutorial/practicals. 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.
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.
Module Texts
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
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
Module Special Admissions Requirements
None
Module Resources
Use of spreadsheets (such as EXCEL) and one sophisticated statistics package (e.g. SPSS)
Module Indicative Content
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.
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.
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.
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.
Module Additional Assessment Details
Portfolio of coursework consisting 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, analysis of data and communication of results assessing Learning Outcomes 1 & 2.
Portfolio of 2 one hour class tests each weighted at 25% assessing Learning Outcomes 1, 3 & 4.
The class test is the final assessment point.
Portfolio of 2 one hour class tests each weighted at 25% assessing Learning Outcomes 1, 3 & 4.
The class test is the final assessment point.