BSEN40860 Chemometrics 1

Academic Year 2024/2025

This module is designed to provide students with a basic understanding of the principles and applications of chemometrics. In this module, students will learn how to analyze and interpret data obtained from various analytical techniques, such as spectroscopy and chromatography, using MATLAB software. The module will cover topics such as experimental design, data preprocessing, and multivariate analysis. By the end of the module, students will have gained the necessary skills to apply chemometric methods to solve some analytical chemistry problems.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to:
(1) Understand the fundamental concepts of the experiment design and principles of chemometrics.
(2) Apply various data preprocessing techniques to prepare data for chemometric analysis.
(3) Calculate distances between objects using different metrics
(4) Apply principal component analysis (PCA) and clustering analysis (CA) techniques to analyze and interpret chemometric data.
(5) Explore data sets, comprehend the experimental design and establish a data analysis protocol for chemical data.

Student Effort Hours: 
Student Effort Type Hours
Lectures

11
Tutorial

8
Autonomous Student Learning

100
Total

119
Approaches to Teaching and Learning:
Active/task-based learning; lectures; reflective learning 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment(Including Essay): The students need to run the Matlab script and submit a report demonstrating their application of statistical techniques and various data preprocessing methods. n/a Graded No

30
Exam (In-person): A final exam consisting of MCQs and Q&A. n/a Graded Yes

40
Assignment(Including Essay): The students need to run the Matlab script and submit a report demonstrating their capability of applying PCA and cluster analysis using Matlab. n/a Graded No

30

Carry forward of passed components
No
 
Resit In Terminal Exam
Summer Yes - 1 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
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