# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

### Timetable information in the Course Catalogue may be subject to change.

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DRPS : Course Catalogue : School of Mathematics : Mathematics

# 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 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
 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.
 Academic year 2022/23, Not available to visiting students (SS1) Quota:  None Course Start Semester 2 Course Start Date 16/01/2023 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
 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 Not entered Keywords Probability,Statistics,PS
 Course organiser Mr Panagiotis Kaklamanos Tel: Email: pkaklama@exseed.ed.ac.uk Course secretary Miss Gemma Aitchison Tel: (0131 6)50 9268 Email: Gemma.Aitchison@ed.ac.uk
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