Final Project Feedback and Grade

[dpmcsuss]

Total
98/125 (78.4%)

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: E

• 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: E

• 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: M

Use more tidyverse functions.

Could be a few more details.

• 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: M

At least use suppressPackageStartupMessages at the top.

Mostly good but a little inconsistent and messy feeling.

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

No context provided.

• 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: R

No real interpretation of the coefficients, only of the overall model.

Including the Prophet model that is so clearly flawed is very problematic. The model predicts huge negative values, which is impossible, and huge swings over time, which seems very unlikely.,

• 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: M

Very minimal and you don't mention the biggest flaw.

• 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: M

I'm not sure why the correlation plot is included.

Generally the plots are OK but not very polished and are low resolution.

• 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: R

You include the correlation matrix but don't really explain it at all.

No interpretations that help to advance evidence for your question of interest.

• 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: R

Remove all instructions.

Not at all self contained.

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

What's your thesis? It just seems like a general EDA without any direction.

Your section on "How can H1B applicants find a job" is written like the applicants have much choice in where they live but they need to get sponsored by an employer first.

• 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: R

Overall, not very polished.

Smooth first figure to better illustrate trends rather than hilighting seasonality. Also hard to see the smaller groups at all. Maybe group them together?

Don't use raw log transformations in map.

Using faceted bar charts doesn't seem like the best choice for Fig 3. Also, no y-axis labels?

• 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: M

Very little effort here.

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: M

No featured image on homepage.

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