Undergraduate Course: Statistics (Yr 3) (MATH09022)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 9 (Year 3 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | This course provides an introduction to the basic concepts of Statistics. The underlying rigorous mathematical framework is provided for analyzing different forms of data and the interpretation of the corresponding results discussed in detail. By the end of the course, students will be able to estimate parameter values for different statistical models and conduct a range of hypothesis tests. |
Course description |
Topics will include :
Sampling distributions
Estimators, including MLEs
Interval estimation
Hypothesis testing
Regression
Analysis of Variance (ANOVA)
In addition the statistical package R will be introduced and used within the course.
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Information for Visiting Students
Pre-requisites | None |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2016/17, 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 20,
Seminar/Tutorial Hours 5,
Supervised Practical/Workshop/Studio Hours 4,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
67 )
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Assessment (Further Info) |
Written Exam
75 %,
Coursework
25 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Coursework 25%, Examination 75% |
Feedback |
Not entered |
Exam Information |
Exam Diet |
Paper Name |
Hours & Minutes |
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Main Exam Diet S2 (April/May) | MATH09022 Statistics (Year 3) | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Ability to apply statistical techniques to problems.
- Ability to interpret the output from statistical analyses.
- Ability to use the statistical computer package R to perform a number of statistical analyses.
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Reading List
Recommended but not essential :
Devore and Berk (2012) Modern mathematical statistics with applications. 2nd edition.
An electronic copy of Devore and Berk is available to download from the University Library.
Rice (1995) Mathematical statistics and data analysis. 2nd edition.
For additional R support :
Crawley (2013) The R Book
An electronic copy of Crawley is available to download from the University Library.
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Additional Information
Graduate Attributes and Skills |
Not entered |
Keywords | StaY3 |
Contacts
Course organiser | Prof Ruth King
Tel: (0131 6)50 5947
Email: Ruth.King@ed.ac.uk |
Course secretary | Mrs Noureen Ehsan
Tel: (0131 6)50 4885
Email: Noureen.Ehsan@ed.ac.uk |
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© Copyright 2016 The University of Edinburgh - 3 February 2017 4:42 am
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