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BSEN30590

Academic Year 2024/2025

MATLAB and R for beginners (BSEN30590)

Subject:
Biosystems Engineering
College:
Engineering & Architecture
School:
Biosystems & Food Engineering
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Professor Aoife Gowen
Trimester:
Autumn
Mode of Delivery:
Online
Internship Module:
No
How will I be graded?
Pass/Fail (GPA Neutral)

Curricular information is subject to change.

This course will introduce students to the use of MATLAB and R for data analysis. MATLAB and R are both high-level scientific programming languages which are frequently used for data organisation, graphical interpretation and statistical analysis, both in academia and industry.

In this module, students will learn how to analyse and manage numerical data in MATLAB and R; construct graphs and tables to interpret numerical and categorical datasets; understand the meaning of variable types and how to interpret and analyse them and develop their own scripts and basic functions for a predefined goal

This module is fully online and assumes no prior knowledge of programming. Through participation in lectures and tutorials, students will learn how to load, visualise and organise data in MATLAB, basic programming concepts, writing scripts and functions. Students will learn how to translate these concepts into the R software environment. By the end of the module, students will have gained the necessary skills to use MATLAB and R for the analysis of a wide range of data types.

About this Module

Learning Outcomes:

On completion of this module, students should be able to:
1. Analyse and manage numerical data in MATLAB and R
2. Construct graphs and tables to interpret numerical and categorical datasets
3. Understand the meaning of variable types and how to interpret and analyse them
4. Develop scripts and basic functions for a predefined goal

Indicative Module Content:

1. Introduction to the MATLAB environment
2. Importing & Exporting data; Tables, Cell Arrays Structures
3. Variables and Assignments; Characters and Strings
4. Matrix Algebra in MATLAB:Vectors and Matrices, Scalar and Array operations
5. Data Visualisation & Graphs in MATLAB
6. Conditional statements, loops and functions in MATLAB
7. Introduction to R studio desktop environment
8. Translating MATLAB commands to R
9. Importing/Exporting data in R
10. Matrix Algebra in R
11. Working with Graphs in R
12. Conditional statements, loops and functions in R

Student Effort Hours:
Student Effort Type Hours
Lectures

10
Tutorial

10
Autonomous Student Learning

80
Total

100

Approaches to Teaching and Learning:
This module is designed to provide students with a practical understanding of the use of MATLAB and R for data analysis. This module assumes no prior knowledge of programming. Students will learn how to load, visualise and organise data in MATLAB, basic programming concepts, writing scripts and functions. Students will learn how to translate these concepts into the R software environment. By the end of the module, students will have gained the necessary skills to use MATLAB and R for the analysis of a wide range of data types.

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): Continuous Assessment based on module content Week 4, Week 8 Pass/Fail Grade Scale No

100

 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring 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

How will my Feedback be Delivered?

Not yet recorded.

Matlab: A Practical Introduction to Programming and Problem Solving , DOI: 10.1016/B978-0-12-804525-1.09993-1
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