Postgraduate Course: Time Series Analysis and Forecasting (MATH11073)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Course type | Standard |
Availability | Not available to visiting students |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 5 |
Home subject area | Mathematics |
Other subject area | Operational Research |
Course website |
http://student.maths.ed.ac.uk |
Taught in Gaelic? | No |
Course description | Filtering, autoregressive and moving average models, ARMA and ARIMA models, forcasting, seasonal variation. The statistical software package SPSS will be used for practical instruction |
Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Additional Costs | None |
Course Delivery Information
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Delivery period: 2013/14 Block 4 (Sem 2), Not available to visiting students (SS1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
Course Start Date |
24/02/2014 |
Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
50
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 6,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 1,
Directed Learning and Independent Learning Hours
31 )
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Additional Notes |
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Breakdown of Assessment Methods (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
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Exam Information |
Exam Diet |
Paper Name |
Hours & Minutes |
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Main Exam Diet S2 (April/May) | | 2:00 | |
Summary of Intended Learning Outcomes
The ability to demonstrate an understanding of the principles behind modern forecasting techniques. The ability to select and appropriate model, to fit parameter values, and to carry out the forecasting calculation, with use of the statistical software package SPSS as appropriate. |
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above. |
Special Arrangements
None |
Additional Information
Academic description |
Not entered |
Syllabus |
week 6 - Introduction, white noise
week 7 - Moving average and autoregressive models
week 8 - ARMA and ARIMA models
week 9 - Forecasting
Week 10 - Seasonal variation and other topics |
Transferable skills |
Not entered |
Reading list |
Not entered |
Study Abroad |
Not entered |
Study Pattern |
Not entered |
Keywords | TSAF |
Contacts
Course organiser | Dr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
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© Copyright 2013 The University of Edinburgh - 13 January 2014 4:41 am
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