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I can see how much effort you made to this project! Especially the 'Proximity' page is well-done with careful examinations about the data set and appropriate visualizations. Maps are impressive in that they provide an easy and clear understanding of your data.
From your project, I learned about the multi-modality methodology. I appreciate the kind explanations you gave throughout the web page.
The results showed in "Multi-modality - Exploring Multi-Modality' page is not that friendly to outside readers. There must be some ways to display the tables in a clear and a reader-friendly way.
Several comments about the contents:
At the first graph in 'Multi-modality' page, you examined that 'for trips that start at stations in proximity with CTA stops, the proportion of Customer trip is noticeably greater for potentially multi-modal trips'. However, for the non-proximity, the same examination can be applied as well. That is, you have to show that there IS a noticeable difference in user type between proximity/non-proximity in order to make your argument persuasive. Same comment applies to the 'When Divvy Trips stop at stations in proximity with CTA stops' part.
It would have been better if you added some implications about the data analysis. First, I am confused about the conclusion. Are you arguing that membership contributes to the usage of Divvy, even if under situations when there are nearby CTA stops? Second, why did you include 'gender', 'birthyear', 'month' variables to the Shiny apps tables? Are they independent variables? In what ways are they related to your project?
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Evaluation of final project by Jongyoon Baik.
Remarks:
The text was updated successfully, but these errors were encountered: