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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Probability and Statistics (MATH11204)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThe 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
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:
  1. demonstrate a conceptual understanding of fundamental concepts of probability and be able to derive basic results from them.
  2. explain their reasoning about probability clearly and precisely, using appropriate technical language.
  3. apply statistical techniques to simple problems.
  4. interpret the output from statistical analyses.
  5. 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
KeywordsProbability,Statistics,PS
Contacts
Course organiserDr Skarleth Carrales Escobedo
Tel:
Email: mcarrale@exseed.ed.ac.uk
Course secretaryMiss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk
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