Postgraduate Course: Incomplete Data Analysis (MATH11185)
Course Outline
| 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 may include :
- types of missingness;
- single and multiple imputation;
- mixture models;
- hidden Markov models; and
- the EM algorithm.
|
Course Delivery Information
|
| Academic year 2019/20, 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 | |
Learning Outcomes
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.
|
Reading List
| Statistical Analysis with Missing Data. Little and Rubin. Wiley. |
Additional Information
| 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 |
Contacts
| Course organiser | Dr Vanda Fernandes Inacio De Carvalho
Tel: (0131 6)50 4877
Email: Vanda.Inacio@ed.ac.uk |
Course secretary | Miss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk |
|
|
University Homepage