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Project Checkpoint Feedback #4

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ShanEllis opened this issue Feb 27, 2024 · 0 comments
Open

Project Checkpoint Feedback #4

ShanEllis opened this issue Feb 27, 2024 · 0 comments

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@ShanEllis
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ShanEllis commented Feb 27, 2024

Project Checkpoint Feedback

Score (out of 5 pts)

Score = 4

Data Checkpoint Feedback

Quality Reasons
Data relevance P Data is relevant to the RQ
Data description P Can shed some light on why you are not considering the other variables other than the key variable?
Data wrangling D Unable to verify if the data is clean. You need to show some sanity check on null values so that I can see that the data is clean.

Comments

Proposal Regrade Feedback

DATA-Ideal dataset description is still not up-to the mark. For the variables, over what time period do you want these data? What is the ideal size of your dataset?

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

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