stat545ubc-2021 / collaborative-ekpereka_mini_data_analysis Goto Github PK

Hi Ekpereka,

Overall, excellent work on your second MDA deliverable! Please see more detailed feedback below:

• Ex 1.1: Great research questions.
• Ex 1.2: Excellent summary tables and visualizations for all four questions, fantastic analysis, and interpretation of the results.
  • Question 3 (graphing): your current levels for age_of_building are sorted alphabetically, which makes it challenging to interpret how window types changes over time - it would be helpful to sort these levels from oldest to youngest buildings.
  • Question 4 (graphing): great small-multiple scatterplots that would benefit from having a best-fit line plotted for each property type. You can add geom_smooth(aes(color=property_type),method="lm", se=FALSE) to do this.
• Ex 1.3: Great analysis.
• Ex 2.1: Great explanation as to why your data is tidy.
• Ex 2.2: Great transformation from tidy to untidy format and from untidy to tidy format.
• Ex 2.3: Excellent use of dplyr functions to produce the desired tibble.
• Reproducibility, readability, and repo organization: Well-organized repo with a good README.md. For Milestone 3, make sure that each milestone in your repo has its own folder. "Files in the Repository" section needs to be expanded to provide a description of each file in your repo. Thanks for knitting your .Rmd as .md document.

Please let me know if you have any questions. Grades will be posted soon on Canvas.

Best,
Albina

Hi Ekpereka,

Excellent work on your third MDA deliverable! Please see more detailed feedback below:

• Ex 1.1: Great use of forcats package to reorder your categorical variable, fantastic plot.
• Ex 1.2: Great illustration of fct_collapse() function to group two categories into the "other" category.
• Ex 2.1: Great use of lm() to build a simple linear regression model.
• Ex 2.2: Great use of the glance() function to get p-value.
• Ex 3.1: Great use of write_csv() and here::here() to save the summary table as a .csv document.
• Ex 3.2: Great use of saveRDS() here::here() to save the model statistics as a .RDS document.
• Tidy submission: Great README.md that orients one well in your repository. Well-organized repo with a great folder structure and knitted .md files for each milestone. Note how none of the README.md files in your individual folders rendered properly when you open the folder because they needed to be titled README.md exactly not README_3.md or README_2.md. Good use of releases to save different versions of your work. Overall, great work!

Please let me know if you have any questions. Grades will be posted soon on Canvas.

Best,
Albina

Hi Ekpereka,

Absolutely fabulous work on your first mini-data analysis deliverable. Please see detailed feedback below.

• Clear and well-structred README.md that orients one well in the repository. Thanks for knitting your .Rmd file and uploading the knitted .md file to your repo! The knitted .md is extremelly organized, very nicely formatted, and overall very easy to read! Loved the table of contents in the beginning.
• Quick note that you can use suppressMessages() around your library() call to avoid showing the messages when loading libraries.
• Ex 1.1: Wonderful summaries and overviews of the four datasets that lists their number of observations + number of variables.
• Ex 1.2: Great use of glimpse(), class(), sum(is.na()) functions to explore the datasets. Very helpful comments summarizing the results which make the knitted .md more readable.
• Ex 1.3: Fantastic justification of the two selected datasets - great graphs that support your choice.
• Ex 1.4: Great exploratory questions for each dataset.
• Ex 2.1: Fantastic exploration of particular variables using different visualization options. Great in-line commenting to explain different parts of your code. Loved the overlapping density plots!
• Ex 2.2: Excellent summaries and explanations of your code and final visualizations.
• Ex 3: Overall, great research questions that you should be able to answer in the next two deliverables.

Please let me know if you have any questions. Grades will be posted tomorrow on Canvas.

Best,
Albina