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BSEN40860

Academic Year 2024/2025

Chemometrics 1 (BSEN40860)

Subject:
Biosystems Engineering
College:
Engineering & Architecture
School:
Biosystems & Food Engineering
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Dr Junli Xu
Trimester:
Autumn
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

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.

About this Module

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 Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
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. Week 14 Graded No
30
 No
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. Week 7 Graded No
30
 No
Exam (In-person): A final exam consisting of MCQs and Q&A. Week 15 Graded Yes
40
 Yes

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. 

Feedback Strategy/Strategies

• Online automated feedback

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Nazan Altun Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 3 Wed 14:00 - 15:50
Autumn Lecture Offering 1 Week(s) - 4, 7 Wed 14:00 - 15:50
Autumn Lecture Offering 1 Week(s) - 5 Wed 14:00 - 15:50
Autumn Lecture Offering 1 Week(s) - 6 Wed 14:00 - 15:50
Autumn Lecture Offering 1 Week(s) - 8, 9, 10, 11 Wed 14:00 - 15:50
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