Data Checkpoint Feedback

[grader-cogs108]

Data Checkpoint Feedback

Score (out of 10 pts)

Score = 10

Data Checkpoint Feedback

	Quality	Reasons
Data relevance	Proficient	- the dataset choice is a little unclear as this seems to be a huge dataset where the relevant rows 'homicide' death seems to be a small subset within. You could motivate why this is the best dataset available for your research question a little better.
Data description	Proficient
Data wrangling	Proficient	- one key wrangling that is missing is the required subsetting. Since your question is concerned only with homicide rate, I would have expected you to filter out any other manners of death. I would have also expected to wrangle your data to aid some of the downstream temporal analysis like maybe putting each entry into a decade bucket so that you can see if patterns change over decades.

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