Peer review

[dmf7]

• Peer review by: Butterflies

• Names of team members that participated in this review: Catherine Purnell, Ryan Silver, Carly Blank, Dolce Feenaghty

• Describe the goal of the project.

There appear to be several goals given that there are two research questions because of a merge conflict, but the main goal appears to be to explain how regular season efficiency correlates to post season and tournament success (shown by seeding)

• Describe the data used or collected, if any. If the proposal does not include the use of a specific dataset, comment on whether the project would be strengthened by the inclusion of a dataset.

The data was collected from a website that includes D1 college basketball stats from 2013-2019, and the dataset was found, not collected.

• Describe the approaches, tools, and methods that will be used.

They used scatterplots to visualize the relationship between their chosen variables and three linear regression models to analyze their data. They mutated the dataset and did not use the mutated dataset?

They used adj.r.squared to analyze the linear models.

• Provide constructive feedback on how the team might be able to improve their project. Make sure your feedback includes at least one comment on the statistical reasoning aspect of the project, but do feel free to comment on aspects beyond the reasoning as well.

The statistical visualizations show a strong logic that gets after their research question. However, there could be more transparent reasoning in the form of a more concrete and thoughtful conclusion. They could also include a visualization that includes a depiction of all three variables, especially given that they conclude an interaction model is the best predictor. They could also add lines of best fit to their original models in order to better demonstrate the correlations.

They could stand to visualize more aspects of the model as well, specifically in relation to postseason success and offensive vs. defensive efficiency.

• What aspect of this project are you most interested in and would like to see highlighted in the presentation.

We are interested in the relationship between offensive and defensive efficiency—from our deductions it seems that high seeds have high offensive and low defensive efficiency, which piques our curiosity.

• Were you able to reproduce the project by clicking on Render Website once you cloned it? Were there any issues with reproducibility?

No, the Render did not work because the data was not loaded in a way that users could access it. For example, there was no read.csv command that would allow users to view the data.

• Provide constructive feedback on any issues with file and/or code organization.

There is no project title; there are some unresolved merge conflicts; the question prompts from the guidelines are still in the report; the code chunks should be labeled and graphs should have titles.

• What have you learned from this team's project that you are considering implementing in your own project?

The idea of comparing the success of numerous methods of modeling the same variables is very interesting, and we will definitely take that into our project!

[angeliequimbo]

Fixed the render by adding read.csv. We will update the workflow discrepancies (labelings and merge conflicts)