Program Overview
Module Overview
This module is intended to introduce basic data handling knowledge and practice combined with introductory programming skills to give students confidence in handling chemical data. The hands-on workshop approach provides students with the chance to solve set problems while building their confidence.
Module Details
Module Provider
Chemistry and Chemical Engineering
Module Leader
SACCHI Marco (Chst Chm Eng)
Number of Credits
15
ECTS Credits
7.5
Framework
FHEQ Level 4
Module Cap
N/A
Student Workload
- Workshop Hours: 22
- Independent Learning Hours: 108
- Guided Learning: 10
- Captured Content: 10
Module Availability
Semester 1
Prerequisites / Co-requisites
None
Module Content
- Introduction to Basic statistical concepts
- Analysis of Variance (ANOVA)
- Parametric vs non-parametric statistics
- Regression
- Graph Plotting and Graphics using current software
- Examples of applications to current research
- A presentation on modern robotics and automation in chemistry
- Basics of Python programming
- Assignment, variables, repetition, making decisions, input/output, graphing in a programming language
- Extended assignment involving writing a python programme to solve a chemical problem
Assessment Pattern
| Assessment Type | Unit of Assessment | Weighting |
|---|---|---|
| Coursework | Python Programming | 50 |
| Coursework | Data Handling Exercise | 50 |
Alternative Assessment
None
Assessment Strategy
The assessment strategy is designed to provide students with a hands-on workshop approach to data handling and programming. The assessments consist of a summative exercise in data handling and an extended coursework in writing a python program to solve an unseen chemical problem.
Module Aims
- To present a selection of modern data handling methods and techniques
- To provide the background necessary for students to comprehend and criticise the results of data analysis
- To give students the opportunity to carry out and comment on a variety of practical data handling examples
- To cover a range of selected topics in a computer programming language
- To cover a range of selected topics in robotics and automation
Learning Outcomes
| Attributes Developed | ||
|---|---|---|
| 001 | Confidently carry out and comment on the results of data handing exercises | KCPT |
| 002 | Comprehend and analyze the results of data handling exercises | KC |
| 003 | Systematically understand the process of computer programming | CP |
| 004 | Can apply appropriate programming skills to solve data analysis problems | KCP |
Attributes Developed
- C - Cognitive/analytical
- K - Subject knowledge
- T - Transferable skills
- P - Professional/Practical skills
Methods of Teaching / Learning
The module will use a workshop-based, hands-on approach. Students will work through set problems in a computer workshop with individual advice from academics and demonstrators available on request.
Programmes this Module Appears In
- Chemistry BSc (Hons) - Semester 1, Optional, requires a weighted aggregate mark of 40% to pass
- Chemistry MChem - Semester 1, Optional, requires a weighted aggregate mark of 40% to pass