Final Project Feedback and Grade

[dpmcsuss]

Total
112/125 (89.6%)

Data Page

• Describe where/how to find data.
  You must include a link to the original data source(s). From what you can tell, why was the data collected/curated? Who collected the data?

Evaluation: M

Where did you get the map data?

• Describe the different data files used and what each variable means.
  If you have many variables then only describe the most relevant ones and summarize the rest. Bulletted lists or tables are recommended.

Evaluation: M

Another table on the secondary data set would be good.

• Describe any cleaning you had to do for your data.
  You must include a link to your load_and_clean_data.R file.
  Also, describe any additional R packages you used outside of those covered in class.
  Describe how you combined multiple data files and any cleaning that was necessary for that.
  Some repetition of what you do in your load_and_clean_data.R file is fine and encouraged if it helps explain what you did.

Evaluation: E

You stick with variable names that your really don't need to, e.g. County...County.Group.

• Organization, clarity, cleanliness of the page
  Make sure to remove excessive warnings, use clean easy-to-read code (without side scrolling), organize with sections, use bullets and other tools, etc.

Evaluation: E

Analysis Page(s)

• Introduce what motivates your Data Analysis (DA)
  Which variables and relationships are you most interested in?
  What questions are you interested in answering?
  Provide context for the rest of the page. This will include figures/tables that illustrate aspects of the data of your question.

Evaluation: M

Why is household weight of interest?

• Modeling and Inference
  The page will include some kind of formal statistical model. This could be a linear regression, logistic regression, or another modeling framework.
  Explain the ideas and techniques you used to choose the predictors for your model. (Think about including interaction terms and other transformations of your variables.)
  Describe the results of your modelling and make sure to give a sense of the uncertainty in your estimates and conclusions.

Evaluation: M

Why is Household Weight the response variable? Isn't that just a sample weighting?

Lots of modeling but interpretations are pretty surface-level.

• Explain the flaws and limitations of your analysis
  Are there some assumptions that you needed to make that might not hold? Is there other data that would help to answer your questions?

Evaluation: E

• Clarity Figures
  Are your figures/tables/results easy to read, informative, without problems like overplotting, hard-to-read labels, etc?
  Each figure should provide a key insight. Too many figures or other data summaries can detract from this. (While not a hard limit, around 5 total figures is probably a good target.)
  Default lm output and plots are typically not acceptable.

Evaluation: R

First plot is OK but it doesn't feel like the best way to represent this data. Maybe stacked bar chart?

Lots of maps that are mostly left to me to interpret. What key insight do they provide.

Default lm output and other overly long output.

• Clarity of Explanations
  How well do you explain each figure/result?
  Do you provide interpretations that suggest further analysis or explanations for observed phenomenon?

Evaluation: M

This ownership correlates with the higher income brackets and educational attainment

This is confusing because that correlation isn't fully evident in the plot. There are other similar examples.

• Organization and cleanliness.
  Make sure to remove excessive warnings, use clean easy-to-read code, organize with sections or multiple pages, use bullets, etc.
  This page should be self-contained.

Evaluation: M

Remove "Our code for this page ...."

Big Picture Page

• Clarity of Explanation
  You should have a clear thesis/goal for this page. What are you trying to show? Provide details that support your thesis but don't go into to much mathematics or statistics. The audience for this page is the general public (to the extent possible).

Evaluation: M

Thesis is OK but doesn't indicate what the disparities are.

• Quality of Figures
  Each figure should be very polished and also not too complicated. There should be a clear interpretation of each figure and each figure should have a clear purpose.

Evaluation: M

First plot is nice.

Has too much going on. Maybe just highlight 2 or 3 education levels.

I don't think the interactive map adds much.

• Creativity
  Do your best to make things interesting. Think of a story. Think of how each part of your analysis supports the previous part or provides a different perspective.

Evaluation: R

Not much of an attempt.

Video

• Video Recording
  Make a video recording (probably using Zoom) providing a quick explanation of your data and demonstrate some of the conclusions from your EDA.
  This video should be no longer than 4 minutes.
  Include a link to your video (and password if needed) in your README.md file on your Github repository. You are not required to provide a link on the website.
  This can be presented by any subset of the team members.

Evaluation: E

Rest of the Site

• General organization and cleanliness of website
  The main title of your page is informative.
  Each post has an author/description/informative title.
  All lab required posts are present.
  Each page (including the home page) has a nice featured image associated with it.
  Your about page is up to date and clean.
  You have removed the generic posts from the initial site template.

Evaluation: E