Projects
Project 1 is completed in MATLAB. Project 2 is completed in R. Students submit a PDF report together with executable source code and machine-readable results. Exact dates, rubrics, and verification details remain under review.
A Two-Language Project Sequence
The projects follow the progression of the course:
- Project 1 uses MATLAB for numerical exploration, curve fitting, residual analysis, and validation.
- Project 2 uses R for data transformation, visualization, statistical modeling, and validation on previously unseen data.
The common real-world problem is building-energy management:
How can temperature and operating conditions help explain and predict the daily heating-energy consumption of a building?
The data are synthetic but realistic. They represent a genuine facilities- management problem but are not actual campus measurements.
What Students Receive
Each team receives data for a different synthetic building. All teams use the same variable definitions and comparable tasks, but the numerical relationships and conclusions differ by group.
The instructor provides:
- a group-specific CSV dataset;
- a data dictionary and problem description;
- a scaffolded MATLAB or R script;
- a report template for Word or Google Docs;
- required output names and examples;
- a later validation dataset for Project 2.
Students are not expected to find a dataset, collect measurements, create a Quarto document, or write HTML.
What Students Submit
| Project | Main software | Required files | Course weight |
|---|---|---|---|
| Project 1: MATLAB Numerical Investigation | MATLAB | PDF report, .m files, project1-results.csv |
10% |
| Project 2: R Modeling and Validation | R | PDF report, .R file, results and validation-prediction CSV files |
10% |
The PDF is the readable report. The source code and CSV outputs make the work reproducible and allow numerical checking across all groups.
Teams and Individual Competence
Teams normally contain three students, giving approximately 20 submissions in a class of 60. Group members may collaborate on the take-home analysis and may use documented AI assistance.
The projects are assessed as group work. Individual competence is established through the quizzes, semester examination, and final examination, which together account for 80% of the course grade.
Every group member remains responsible for understanding the submitted code, figures, calculations, and conclusions. Each submission includes a contribution statement signed by all group members.
Possible Project Verification
After a project is submitted, any student may be invited to a brief individual verification. Selection may be random or may occur because a material inconsistency in the code, results, report, or contribution statement requires clarification. Selection does not imply suspected misconduct.
The verification normally lasts five to ten minutes and concerns only submitted work. A student may be asked to explain a code fragment, interpret a figure or result, describe a contribution, or reproduce a small modification.
A difference between project and examination performance may prompt review, but does not by itself establish academic misconduct. Unresolved concerns are handled through the university’s academic-integrity procedures.
How the Work Is Checked
The common file structure permits two complementary checks:
- Automated check: rerun the MATLAB or R code and independently verify row counts, summaries, coefficients, prediction errors, and saved results.
- Report review: inspect the PDF for appropriate figures, correct interpretation, honest limitations, and agreement between the prose and the computation.
The instructor retains final responsibility for qualitative judgments and grades.