| CODE | SOR0510 | ||||||||||||
| TITLE | Statistical Methods for Information and Communication Technology | ||||||||||||
| UM LEVEL | 00 - Mod Pre-Tert, Foundation, Proficiency & DegreePlus | ||||||||||||
| MQF LEVEL | 4 | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||||||
| DESCRIPTION | The study-unit will have the following topics: - Familiarisation with R and SPSS; - Parametric tests; - Non parametric tests; - Regression; - Generalised Linear Models; - Principal components and factor analysis; - Discriminant analysis; - Techniques in time series analysis; - Stochastic simulation; - Applications in Queuing theory. As can be seen in the above list of topics, some of these topics are already covered in SOR0233, and students taking this study-unit will be attending SOR0233 lectures (along with other students registered for this unit) in the first semester and submitting the project related to this study-unit. Since SOR0233 is a 2 ECTS study-unit, the grade related to this project will have a 40% weighting in the global grade. The other topics will be covered in the second semester, in 21 hours of lectures, and another project related to the remaining topics will be given. This project will have a weighting of 60% of the global grade. Study-Unit Aims: The aim of this study-unit is to provide postgraduate students of CIS with additional statistical skills to those obtained in their undergraduate courses. These includes standard modelling and hypothesis testing in SPSS (a statistics software) and R (a statistics programming language), and additional techniques which are of specific interest to CIS students. The layout of this study-unit has been meticulously discussed with the department of CIS to ensure that the course content matches the needs of the CIS student. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to understand the concepts behind the various advanced statistical techniques mentioned above, and their purpose within the context of computer information systems. 2. Skills: By the end of the study-unit the student will be able to: - implement the statistical techniques mentioned above; - gain experience with using SPSS and R to implement same statistical techniques. Main Text/s and any supplementary readings: - Field, A. , Miles, J. and Field, Z. (2012). Discovering Statistics Using SPSS for WIndows: Advanced Techniques for Beginnners. Sage Publications Ltd. -The R Manuals: https://cran.r-project.org/manuals.html. - Asmussen, S. and Glynn, P. (2007) Stochastic Simulation: Algorithms and Analysis. Springer. - Kelton, W.D. (2006). Simulation with Arena. McGraw-Hill. |
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| STUDY-UNIT TYPE | Lecture and Project | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Mark A. Caruana Maria Kontorinaki Fiona Sammut Monique Sciortino David Paul Suda |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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