# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Mathematics : Mathematics

# Postgraduate Course: Incomplete Data Analysis (MATH11185)

 School School of Mathematics College College of Science and Engineering Credit level (Normal year taken) SCQF Level 11 (Postgraduate) Availability Not available to visiting students SCQF Credits 10 ECTS Credits 5 Summary This course is for MSc students who already have some undergraduate level background in statistics. The course focuses on different techniques for dealing with missing data within a formal frequentist statistical framework. Course description Topics to be covered include : - types of missingness; - single and multiple imputation; - mixture models; - hidden Markov models; and - the EM algorithm.
 Pre-requisites Students MUST have passed: Statistical Methodology (MATH10095) OR ( Linear Statistical Modelling (MATH10005) AND Likelihood (MATH10004)) Co-requisites Prohibited Combinations Other requirements None
 Academic year 2017/18, Not available to visiting students (SS1) Quota:  None Course Start Semester 1 Timetable Timetable Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 ) Assessment (Further Info) Written Exam 95 %, Coursework 5 %, Practical Exam 0 % Additional Information (Assessment) Coursework 5%; Examination 95% Feedback Not entered Exam Information Exam Diet Paper Name Hours & Minutes Main Exam Diet S1 (December) Incomplete Data Analysis (MATH11185) 2:00
 On completion of this course, the student will be able to: understand different types of missingness.understand different statistical techniques for dealing with missing data and associated advantages and disadvantages.fit models to data with missing observations.interpret the output from statistical analyses.
 Statistical Analysis with Missing Data. Little and Rubin. Wiley.
 Graduate Attributes and Skills Not entered Special Arrangements These Postgraduate Taught courses may be taken by Undergraduate students *without* requiring a concession (NB. students on Postgraduate taught programmes are given priority in the allocation of places). For all other Postgraduate Taught courses the student and/or Personal Tutor must seek a concession. Keywords IDAn,Data Analysis,Statistics
 Course organiser Dr Vanda Fernandes Inacio De Carvalho Tel: (0131 6)50 4877 Email: Vanda.Inacio@ed.ac.uk Course secretary Mrs Frances Reid Tel: (0131 6)50 4883 Email: f.c.reid@ed.ac.uk
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