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BSEN40870

Academic Year 2024/2025

Chemometrics 2 (BSEN40870)

Subject:
Biosystems Engineering
College:
Engineering & Architecture
School:
Biosystems & Food Engineering
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Professor Aoife Gowen
Trimester:
Spring
Mode of Delivery:
Online
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This course will provide students with an advanced understanding of the principles and applications of chemometrics. Chemometrics, defined by IUPAC as “the application of statistics to the analysis of chemical data (from organic, analytical or medicinal chemistry) and design of chemical experiments and simulations”, has become a scientific discipline in its own right, and is employed widely for the analysis of multivariate data in analytical chemistry.

In this module, students will learn how to analyze and interpret data obtained from various analytical techniques, such as spectrometry, using chemometric tools in the MATLAB environment. The module will cover topics such as regression, classification, validation and variable selection and the underlying theory will be illuminated through the use of real world examples. By the end of the module, students will have gained the necessary skills to apply advanced chemometric methods to real word multivariate data.

Through participation in lectures and tutorials, students will be able to understand the fundamental concepts and principles of key regression and classification techniques, and will develop methods to optimise and evaluate chemometric techniques.

About this Module

Learning Outcomes:

On completion of this module, students should be able to:
1. Understand the fundamental concepts and principles of PLS, PCR, ILS and CLS regression.
2. Apply classification techniques to multivariate data using 2 class, 1 class or multiclass classifiers.
3. Analyse, optimise and validate regression and classification models
4. Apply variable selection to identify and interpret the most important variables in a regression or classification problem.
5. Evaluate a selection of chemometric techniques to achieve a pre-defined goal.

Indicative Module Content:

1. Mathematical basis, applications and limitations of univariate & multivariate calibration
2. Classical Least Squares, Inverse Lease Squares, Multivariate linear regression with interaction terms
3. Mathematical basis, applications and limitations of Ridge regression, principal components regression and partial least squares regression
4. Outlier evaluation, detection and removal
5. Cross validation for model building and optimisation
6. Mathematical basis & application of 1, 2 and multi-class classification techniques (e.g. LDA, QDA, PLS-DA, SIMCA)
7. Commonly used methods of variable selection
8. Application of variable selection to multivariate data and interpretation the results
9. Analysis of multivariate data from diverse sources
10. Development of MATLAB scripts for full dataflow

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

80

Lectures

12

Tutorial

10

Total

102


Approaches to Teaching and Learning:
Lectures, tutorials, individual assignments

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): Assignment on application of chemometric techniques to data Week 6, Week 15 Graded No
50
No
Exam (In-person): Exam on topics covered in module End of trimester
Duration:
1 hr(s)
Graded No
50
No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Comprehensive chemometrics: chemical and biochemical data analysis by Brown, Steven D; Tauler i Ferré, Romà; Walczak, Beata. 2020, Second edition.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 11:00 - 12:50