Unit name | Applied Statistics |
---|---|
Unit code | EMAT30007 |
Credit points | 10 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Dr. Simini |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
None |
School/department | School of Engineering Mathematics and Technology |
Faculty | Faculty of Engineering |
The unit is designed to provide students with practical experience in using statistical methodologies to solving real-world problems. The key word in the unit is “practical.” A focus on both real data and simulated realistic data will be a major component of the applied statistics unit. Each concept will be taught in a bottom-up way that will allow students to understand the vital role of the field of probability and statistics in academic and industrial engineering research.
Aims: To give students a thorough grounding in statistical methodologies and to enable students to use these techniques to answer questions about real world data from engineering / applied science.
1. Use discrete and continuous probability distributions, sampling distributions, simple and multivariate linear regression. Understand classical statistical inference and have an appreciation of model comparison.
2. In addition to covering more advanced topics related to traditional multiple regression/correlation, the students will understand logistic regression, experimental design, reliability data analysis and bootstrap techniques.
3. Experience of applying statistical techniques to data.
4. Select statistical methodologies for new and unfamiliar problems and justify their use.
5. Practise interpreting the results obtained from using of statistical methodologies.
One lecture (1hr) and one lab (2 hrs) per week
50% Summer Exam (1.5 hr) MUST PASS
50% coursework consisting of two assessed projects each worth 25% MUST PASS MUST PASS
W.Mendenhall & T. Sincich, "Statistics for Engineering and the Sciences", CRC Press, 2016.