Project Checkpoint Feedback

[ShanEllis]

Project Checkpoint Feedback

Score (out of 5 pts)

Score = 5

Data Checkpoint Feedback

	Quality	Reasons
Data relevance	P
Data description	P	The data types of the features have not been mentioned. Not deducting points for this as of now. You do not need to provide explanation for all feature names, especially for the ones that you would be dropping.
Data wrangling	U	Did you miss out on adding the data cleaning parts? You do talk about removing and renaming a few columns, but is not visible in the code structure.

Comments

Proposal Regrade Feedback

	Quality	Reasons
Abstract	NA
Research question	D	What age group are we talking about here?
Background	P
Hypothesis	P
Data	D	Misses talking about the ideal dataset in the new analysis. Since it is a new question, you could need to mention the ideal dataset requirements as well. Could you also expand on how old the data is, or from which year it is?
Ethics	E
Team expectations	E
Timeline	P

Rubric

	Unsatisfactory	Developing	Proficient	Excellent
Data relevance	Did not have data relevant to their question. Or the datasets don't work together because there is no way to line them up against each other. If there are multiple datasets, most of them have this trouble	Data was only tangentially relevant to the question or a bad proxy for the question. If there are multiple datasets, some of them may be irrelevant or can't be easily combined.	All data sources are relevant to the question.	Multiple data sources for each aspect of the project. It's clear how the data supports the needs of the project.
Data description	Dataset or its cleaning procedures are not described. If there are multiple datasets, most have this trouble	Data was not fully described. If there are multiple datasets, some of them are not fully described	Data was fully described	The details of the data descriptions and perhaps some very basic EDA also make it clear how the data supports the needs of the project.
Data wrangling	Did not obtain data. They did not clean/tidy the data they obtained. If there are multiple datasets, most have this trouble	Data was partially cleaned or tidied. Perhaps you struggled to verify that the data was clean because they did not present it well. If there are multiple datasets, some have this trouble	The data is cleaned and tidied.	The data is spotless and they used tools to visualize the data cleanliness and you were convinced at first glance

Grading Rules

Scoring: Out of 5 points

Each Developing => -1 pts
Each Unsatisfactory=> -2 pts
until the score is 0

If students address the detailed feedback in a future checkpoint they will earn these points back

DETAILED FEEDBACK should be left in the data section AND anywhere the student addressed proposal feedback but did not do it to your satisfaction

[minhnhat1901]

We are done fixing all missing part from the Project Checkpoint