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UNIVERSITY OF KENT MODULE SPECIFICATION TEMPLATE SECTION 1: MODULE SPECIFICATIONS 1. Title of the module Data Mining and Forecasting (CB9040) 2. School or partner institution which will be responsible for management of the module Kent Business School 3. Start date of the module Spring of 2011, updated for January 2015 4. The number of students expected to take the module 30 - 80 5. Modules to be withdrawn on the introduction of this proposed module and consultation with other relevant Schools and Faculties regarding the withdrawal None 6. The level of the module (e.g. Certificate [C], Intermediate [I], Honours [H] or Postgraduate [M]) Level M 7. The number of credits and the ECTS value which the module represents 15 credits (7.5 ECTs) 8. Which term(s) the module is to be taught in (or other teaching pattern) Spring 9. Prerequisite and co-requisite modules CB969, or equivalently, fundamentals of statistics for management and business 10. The programmes of study to which the module contributes MSc Management Science and MSc Business Analytics 11. The intended subject specific learning outcomes 11.1 Apply statistical techniques that deal with data mining and forecasting 11.2 Analyse the results accurately and present the outcomes in a way that is a wider audience can understand 11.3 Use of statistical software SPSS for real life data 11.4 Understand and critically discuss research issues within the area of data mining 12. The intended generic learning outcomes 12.1 Being able to think critically and be creative 12.2 The ability to conduct research into business and management issues either individually or as part of a team through research design, data collection, preparation, analysis, 1 UNIVERSITY OF KENT synthesis, and reporting 12.3 Using information and knowledge effectively by scanning and organising data, synthesising and analysing in order to abstract meaning from information and to share knowledge 12.4 Effective use of ICT 13. A synopsis of the curriculum Exploratory data analysis Graphical Techniques, Distribution fitting, Testing for normality, choosing the most appropriate test, interpreting the results. Association Tests of association (Chi-square tests) Measures of association (Goodman-Kruskal’s gamma, Kendal Tau) Discovery of relationship between variables in large datasets Regression and Classification Multiple linear regression, Classification, and their performance measures Clustering and factor analysis Factor analysis; cluster analysis Time series modelling The Holt-Winters approach, the Box-Jenkins approach Data mining process model Cross Industry Standard Process for Data Mining (CRISP-DM) The computer package SPSS will be used for this course including EXCEL in some occasions. 14. Indicative Reading List Most will be based on specially designed class experiences and specially written lecture notes. Students will have to read papers from the Journal of the Operational Research Society, Operational Research Insight, Interfaces, the Journal of Forecasting, the International Journal of Forecasting, Omega, and others as the opportunity arises. Some books that are of relevance, but students will not be required to purchase are: Witten, I.H, Eibe F. and Hall, M.A. (2011) Data Mining: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems). Hair, J, et al (2005), Multivariate Data Analysis (6th ed.) Prentice Hall, NY Makridakis, S., Wheelwright, S.C. and Hyndman, R.J. (1998). Forecasting. Wiley. O’Donovan, T.M. (1983). Short term forecasting. Wiley. Box, G.E.P. and Jenkins, G.M. (1970) Time Series Analysis. Holden Day. Lewis, C.D. (1975). Demand analysis and inventory control. Saxon House. Harvey, A.C. (1981). Time series models. Academic Press. 15. Learning and Teaching Methods, including the nature and number of contact hours and the total study hours which will be expected of students, and how these relate to achievement of the intended module learning outcomes: 2 UNIVERSITY OF KENT Hours Subject LOs Generic LOs Lectures 24 11.1 – 11.4 - Terminals 24 11.1 – 11.4 12.2 – 12.4 Independent study 102 11.1 – 11.4 12.1 - 12.4 Total hours 150 16. Assessment methods and how these relate to testing achievement of the intended module learning outcomes Weighting Subject LOs Generic LOs Two In-Class Open Book Tests 30% each 11.1, 11.2, 11.3 12.1 – 12.4 One data analysis report – 1000 words 40% 11.1, 11.2, 11.3 12.1 – 12.4 17. Implications for learning resources, including staff, library, IT and space A computer with SPSS installed for each student in the terminal 18. The School recognises and has embedded the expectations of current disability equality legislation, and supports students with a declared disability or special educational need in its teaching. Within this module we will make reasonable adjustments wherever necessary, including additional or substitute materials, teaching modes or assessment methods for students who have declared and discussed their learning support needs. Arrangements for students with declared disabilities will be made on an individual basis, in consultation with the University’s disability/dyslexia support service, and specialist support will be provided where needed. 19. Campus(es) where module will be delivered: Canterbury SECTION 2: MODULE IS PART OF A PROGRAMME OF STUDY IN A UNIVERSITY SCHOOL Statement by the School Director of Graduate Studies: "I confirm I have been consulted on the above module proposal and have given advice on the correct procedures and required content of module proposals" ................................................................ .............................................. Director of Graduate Studies Date ………………………………………………… Print Name Statement by the Head of School: "I confirm that the School has approved the introduction of the module and, where the module is proposed by School staff, will be responsible for its resourcing" ................................................................. .............................................. Head of School Date ……………………………………………………. 3 UNIVERSITY OF KENT Print Name Module Specification Template Last updated February 2013 4