CME1027 : Data Analysis in Process Industries
- Offered for Year: 2024/25
- Module Leader(s): Mr Joseph Dessi
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 5 |
| ECTS Credits: | 3.0 |
| European Credit Transfer System | |
Aims
To provide students with a fundamental understanding of the basic statistical techniques (summary statistics, probability distributions, interval estimation and regression analysis) routinely used in the chemical, process, and engineering industries.
This course provides the basis for all subsequent statistical modules by introducing the fundamental statistical tools to undertake a preliminary statistical analysis of any data. More specifically the course introduces basic statistical tools that enable data to be presented, described and interpreted in an appropriate and statistically robust manner.
Outline Of Syllabus
Introduction: Descriptive statistics;
Probability: probability theory; probability distributions (continuous and discrete); normal distribution; Statistical Inference and hypothesis testing: Sampling distributions and confidence intervals – One sample problems (mean, standard deviation, paired comparisons) and Two sample problems
Regression analysis: method of least squares.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Exam revision |
| Guided Independent Study | Assessment preparation and completion | 1 | 1:30 | 1:30 | Exam |
| Structured Guided Learning | Academic skills activities | 1 | 1:00 | 1:00 | Excel walkthrough videos |
| Structured Guided Learning | Academic skills activities | 1 | 7:00 | 7:00 | Tutorial questions |
| Scheduled Learning And Teaching Activities | Practical | 1 | 1:00 | 1:00 | Computer practical |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 5 | 1:00 | 5:00 | Drop-in tutorials |
| Guided Independent Study | Independent study | 1 | 13:30 | 13:30 | Review course material |
| Total | 50:00 |
Teaching Rationale And Relationship
In-person lectures convey the statistical concepts and theory and their application in process engineering. Tutorial questions will be supplied for students' to work through each week. Drop-in tutorials will be used to address student queries and aid understanding. Short video walkthroughs of Excel will help demonstrate how to use software to carry out data analysis.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Digital Examination | 90 | 2 | A | 90 | NUMBAS Statistics exam, in person |
Exam Pairings
| Module Code | Module Title | Semester | Comment |
|---|---|---|---|
| Mathematical Modelling & Statistical Methods For Engineering | 2 | N/A |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 2 | M | 10 | Statistics in-course NUMBAS assessment |
Assessment Rationale And Relationship
The examination enables the assessment of whether the students have understood the methodologies and whether they are sufficiently conversant with the application of the techniques to real world scenarios.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CME1027's Timetable