hw02 ready for grading

[Jenncscampbell]

@vincenzocoia @gvdr @ksedivyhaley @joeybernhardt @mynamedaike @pgonzaleze @derekcho @navysealtf9k

[ghost]

Hello Jenncscampbell,

I think you did a solid job.

Reading through your readme page helped me grasp what your reasoning and approach was going through the assignment. I found your description of the View function from your readme to be informative. Similarly including a link from your readme to your data analyses was a practical utility.

The data analysis and exploration itself was sturdy. You provided interpretation in addition to function output thereby making it easier for a potentially new user to know what piece was relevant for a specific question. Sometimes code was not visible to the viewer in the .md file, but was included in the .rmd file (e.g. the first histogram). Not overburdening the viewer with code while still keeping it accessible is a fine balance to maintain, for the present reader you hit the balance well.

I think your discovery that Oceania had the least number of data points was intriguing given the magnitude of difference. Even if Oceania had ten times more data points it would still be the continent with the least data points. A scrupulous observation on your end to document. One slightly confusing aspect of this table is the inclusion of NA without an interpretation to the viewer of what this means. There is also a minor point in having an extra blank column in the table.

You included various different graph types and functions, including filter, select and mutate. Something unique however was that in addition to using transparency, you applied geom_jitter in your graphs to make more visible overlapping or stacking data points. In your final graph you also removed the default grey background of ggplot showing consideration of different aesthetics. I noticed for the final portion of the assignment you also had “### Other notes:” text, which I assume was to create a new section but perhaps had included an extra space. These obviously minor points aside a strong submission.

[navysealtf9k]

HI @Jenncscampbell,

• I liked your organization of your exploration. Your README file provided a great template of how to report on the difficulties encountered with each task and made your thoughts and goal for the assignment very tractable. I hope to make use of this method for my upcoming homework assignments.

• Your code structure was good. You made extensive use of the dplyr and ggplot packages as required by the assignment. Your investigation into each variable with the aid of graphs and tables made your conclusions easy to asses and verify. I like how you utilized ggplot to produce your graphics, namely the box plot of continent against population. I liked how you coloured the outliers to get across your point on the large population size of Asia. Furthermore I learned of new function (geom.jitter) to overcome the problem of over plotting. This is something that I feel like would be very handy for me to make use in my current plots in HW03 (thanks for that 👍 ).

• When switching in between sections, It felt a bit difficult for me to understand how you selected your variables. May I suggest picking a subset of the data initially and then building on an analysis of it as you answer the tasks. I feel like that would provide a great story to your excellent analysis skills.

Overall I think you did a good job and I look forward to having an opportunity to review your work again.

Regards