D599 – Data Preparation and Exploration

D599 Data Preparation and Exploration

Colleges: School of Technology

This dataset includes only posts filtered for negative sentiment. Counts reflect discussion volume (posts), not students, and do not measure satisfaction.

Reported difficulty posts
2

Negative-sentiment posts
3

Recurring patterns
2

Recurring patterns

grading_or_answer_key_or_process_issues

1 posts Common theme Search posts

Rubric wording or evaluator guidance is ambiguous or misapplied (identifier variables incorrectly labeled as quantitative)

I just got sent back my Task 1 for revision because they said EmployeeNumber is Quantitative and NOT Qualitative? ... EmployeeNumber is considered an identifier and should therefore be labeled Qualitative Nominal
Open post

Insufficient or low-quality instructional materials

1 posts Common theme Search posts

Provided datasets contain missing/dirty data but tasks and instructions do not specify or guide data cleaning expectations

[Did any one clean the health insurance data that was given before starting the visualization and stats of the project? I noticed there was missing data but this task is not particularly focused on it.]
Open post

Note: post_excerpts.json was not available at build time, so some Open post links may fall back to a generic Reddit URL.