Probability Theory and Mathematical Statistics (UESTC) UESTCHN2009
- Academic Session: 2023-24
- School: School of Engineering
- Credits: 14
- Level: Level 2 (SCQF level 8)
- Typically Offered: Semester 1
- Available to Visiting Students: No
Short Description
The objective of this course is to introduce the basic concepts of probability and statistics. It ranges from interpretation of probability, conditional probability, random variables and distributions, expectation, parameter estimation, testing of hypotheses, to the linear regression analysis.
Timetable
Course will be delivered continuously in the traditional manner at UESTC.
Requirements of Entry
Mandatory Entry Requirements
None
Recommended Entry Requirements
None
Excluded Courses
None
Co-requisites
None
Assessment
Assessment
25% homework and unit tests, 75% closed-book final exam (2 hours)
Reassessment
In accordance with the University's Code of Assessment reassessments are normally set for all courses which do not contribute to the honours classifications. For non honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students, and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions are listed below in this box.
Due to the nature of the coursework and sequencing of courses, it is not possible to reassess the coursework project and laboratory.
Main Assessment In: December
Course Aims
This course aims to develop a sound theoretical base in probability and statistics and show how these are applied in a range of contexts from engineering.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
explain the basic concepts of probability theory;
explain the basic concepts of mathematical statistics;
describe the distribution of random variables;
describe the numerical characteristic of random variable;
demonstrate how the law of large numbers leads to the central limit theorem;
estimate parameters from given data;
test a hypothesis from given data
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.