Postgraduate Course: Probability and Statistics (MATH11204)
|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
|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.
- Axioms; basic laws of probability.
- properties; discrete and continuous distributions; central limit theorem.
Point and interval estimation
- Unbiased and consistent estimators; confidence intervals.
- 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
Entry Requirements (not applicable to Visiting Students)
||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 2020/21, Not available to visiting students (SS1)
|Course Start Date
|Learning and Teaching activities (Further Info)
Online Activities 30,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework : 100%
|No Exam Information
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.
|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.
|Graduate Attributes and Skills
|Course organiser||Mr David Elliott
|Course secretary||Miss Gemma Aitchison
Tel: (0131 6)50 9268