Department of Electrical Engineering and Electronics
ELEC362
Project
Linear regression application
Module ELEC362
Coursework name Project
Component weight 50%
Semester 1
HE Level 5
Lab location personal computers/laptops, university remote computer
Work Individual
*Estimated time to finish 40 hours (coding and testing)
Assessment method Individually
Submission format Online via VITAL
Submission deadline 11.59 pm on the 17th January, 2021
Late submission Standard university penalty applies
Resit opportunity None except for extenuating circumstance
Marking policy Marked and moderated independently
Anonymous marking No (the marker needs to link the code to the report)
Feedback via VITAL GradeMark® / Turnitin Feedback Studio
Expected release of marks date 15 business days from the deadline
Learning outcomes LO2: Using C++ to implement GUI-based software.
LO3: Using online documentation for self-learning.
*Note: This estimate may vary based on the need to debug your application. Make sure
you start working on the project as soon as possible.
Page 2 of 5
The project
Task 1: Design and implement a Qt-based GUI linear regression application. The application reads a
file of data points, given by two columns one for x coordinates and one for y coordinates, then
calculates the best linear fit of the form: