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Module Descriptor School of Computer Science and Statistics

Module CodeST3002
Module Short Title
Semester TaughtSemester 1
Contact Hours1 hour lecture and 2 hours of lab per week
Module PersonnelJason Wyse
Learning OutcomesAfter this course, students will have a toolbox of skills for data analysis. In particular, students should be able to apply their statistical knowledge to a given real scenario, do analysis and make recommendations.
Learning AimsThis module aims to provide an opportunity for students to develop their hands on skills in data analysis. Specific methods will be explored to illustrate these approaches. Students will become very familiar with the R statistical computing language.
Module ContentStatistical computing in R Merging datasets Simulation Optimisation Generalized linear models Distributions
Recommended Reading List
Module PrerequisitesEngineering Mathematics III Applied Statistics Applied Probability.
Assessment DetailsAssessment is by continuous assessment only. To pass the module, students must achieve an overall mark of 40%. 
Module Website
Academic Year of Data2016/17