Undergraduate Course: Statistical Communication Skills (MATH10070)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Compulsory course for the Honours Degrees in Mathematics & Statistics and Economics & Statistics. Students must have a strong background in statistics and have previously taken Linear Statistical Modelling (MATH10005) AND Statistics (Year 2) (MATH08051), and be taking Likelihood (MATH10004). The workshops will involve application of statistical methods covered in these statistics courses, as well as other models introduced in the course. |
| Course description |
Use of the R language for statistical modelling and graphics, particularly for regression and one-way and two-way analysis of variance; writing and presenting statistics; project work.
Linear statistical models and residual analyses in the R language.
One-way analysis of variance.
Two-way analysis of variance with replication.
Two-way analysis of variance without replication.
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2017/18, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 4,
Seminar/Tutorial Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
74 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 100% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Ability to use the R language to fit regression and analysis-of-variance models, to examine residuals from such models, and to investigate transformations of data.
- Be able to apply the theory in other statistics courses to challenging problems.
- Ability to analyse data and interpret results of statistical analyses.
- Ability to present a typeset report of an individual statistical project.
- Ability to deliver an oral presentation.
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Reading List
Recommended, not essential:
(1) Montgomery, D.C., Design and Analysis of Experiments, Wiley, 2005.
Montgomery, D.C., Design and Analysis of Experiments, Wiley, 2005. ISBN: 9781118097939
http://bookshop.blackwell.co.uk/jsp/id/Design_and_Analysis_of_Experiments/9781118097939
(2) Cox, D.R., Planning of Experiments, Wiley, 1958. £92.95 ISBN: 9780471574293 New Edition in Print (1958 edition out of print)
http://bookshop.blackwell.co.uk/jsp/id/Planning_of_Experiments/9780471574293
(3)Krzanowski, W., An Introduction to Statistical Modelling, Arnold, 1998.
£31.50 ISBN: 9780470711019 New Edition
http://bookshop.blackwell.co.uk/jsp/display_product_info.jsp?isbn=9780470711019
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | SCS |
Contacts
| Course organiser | Prof Finn Lindgren
Tel: (0131 6)50 5769
Email: |
Course secretary | Mrs Noureen Ehsan
Tel: (0131 6)50 4885
Email: |
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