Data Checkpoint Feedback

[grader-cogs108]

Data Checkpoint Feedback

Score (out of 10 pts)

Score = 6

Data Checkpoint Feedback

	Quality	Reasons
Data relevance	Developing	This is a great start, however your hypothesis mentions controlling for population density and socioeconomic factors, including poverty rate, unemployment rate, and median income, yet these metrics are not included in your datasets.
Data description	Proficient
Data wrangling	Developing	Are you able to produce output cells to illustrate the integrity of the data, metric distribution, proportion of nulls, etc?

Note: In your data_checkpoint, you were graded on a description of an ideal dataset, but now you're being graded on an actual dataset. If you earn full marks on data relevance and description here, 50% of previous points lost previously on the Data section will be returned on your data_checkpoint...even though you aren't including information on your ideal dataset any longer. If full marks are not earned here, no points will be returned.

PLA Comments

No additional comments.

Data Checkpoint Regrade Feedback

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 10 points

Each Developing => -2 pts
Each Unsatisfactory=> -4 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 data_checkpoint feedback but did not do it to your satisfaction