Marking Scheme for MH4510 Lab Reports

Marking scheme

You will get “excellent”, or 100% for this lab report if everything is perfect. You will get “good”, or 75% if there are minor issues such as

• Using explicit loops when it is not really needed (which is very rare)
• Using base R for data wrangling or plotting instead of tidyverse pipelines when a tidyverse solution was explicitly taught in the lab.
• Re-inventing the wheel, i.e., implementing your own versions of built-in functions from scratch.
• Not answering verbal questions to the point

You will get “average”, or 50% if there are serious issues in your report, such as

• Not doing data normalization when it is needed
• Not splitting the data into training and test sets for training ML models
• Missing one question entirely

You will get “poor”, or 25% if you barely attempt this report. Examples of this are

• Submitting your report without the output of R codes
• Just doing one of two questions out of the four
• Giving nonsensical answers to all questions

You will get “not done”, or 0% if you do not attempt this report, if you fail to declare AI usage when you have actually used generative AI, or if you copy another student’s answer.

It is okay to use generative AI and it is okay to discuss these questions with your peers, but in the end of the day, this is indivudual work and you are responsible for it.