Postgraduate Course: Probability and Statistics (MATH11204)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The course is delivered online.
This course is an optional course for students studying on the Data Science, Technology and Innovation (DSTI) online distance learning programme.
The course gives an introduction to Probability and Statistics. |
| Course description |
Probability
- Axioms; basic laws of probability.
Random variables
- properties; discrete and continuous distributions; central limit theorem.
Point and interval estimation
- Unbiased and consistent estimators; confidence intervals.
Hypothesis testing
- Type I and II errors; p-values; normal and t-tests.
Regression and correlation
- Correlation; linear regression; hypothesis tests; confidence intervals.
Introduction to practical R
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Availability - only available to students studying on the Data Science, Technology and Innovation (DSTI) online distance learning programme. |
Course Delivery Information
|
| Academic year 2024/25, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 2 |
| Course Start Date |
13/01/2025 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Online Activities 30,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
68 )
|
| 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:
- demonstrate a conceptual understanding of fundamental concepts of probability and be able to derive basic results from them.
- explain their reasoning about probability clearly and precisely, using appropriate technical language.
- apply statistical techniques to simple problems.
- interpret the output from statistical analyses.
- use the statistical computer package R to perform a number of statistical analyses.
|
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. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Probability,Statistics,PS |
Contacts
| Course organiser | Dr Skarleth Carrales Escobedo
Tel:
Email: mcarrale@exseed.ed.ac.uk |
Course secretary | Miss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk |
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