HW03 ready for grading

[Mathnstein]

@vincenzocoia @gvdr @ksedivyhaley @JoeyBernhardt @mynamedaike @pgonzaleze @derekcho

[ghost]

Hello @Mathnstein ,

This my peer review for your Hw03. Your README.md file is clear enough and contains the proper links to each one of the assignments we have done so far. You could add the md file as well, besides the pdf one. I find the md file easier to navigate in, just a personal opinion. I like that the pdf contains the general instructions at the beginning, good idea! Now, let's go to your task list:

1. Get the maximum and minimum of GDP per capita for all continents. The idea of taking the log-transformation on the response GDP is pretty clever, because this will give a clearer idea on the data spread and distribution regardless of the many outliers. However, you could have kept the original response gdpPercap which is a metric already adjusted by the country's population. You could also have used ggplot2() instead of the the boxplot() function.

2. Look at the spread of GDP per capita within the continents. Again, the log-transformation in the response is a really good idea to check the data spread. Maybe, I would include a time series per continent, in order to check the gdpPercap evolution over time. I did it on my assignment, but on the original response. Now, I'm curious about the log-transformation... thanks for the idea! 🙂

3. How is life expectancy changing over time on different continents? I totally liked how you incorporated regression analysis on the evolution over time per continent. An inclusion of side-by-side boxplots could be a good idea in this case. Good job on the facet use on ggplot().

In general, you fulfilled the requirements in each task while providing useful interpretations for each case. You could have detailed a little but more about the data extraction and plotting processes in each task, that gives the reader a clearer picture about what's going on the assignment.

Cheers,

Alexi

[NSKrstic]

Peer Review:

Further Gapminder Dataset Exploration:

• Successfully completed 3 different tasks, and appropriately uses dplyr and ggplot for most of the tasks.
• For the first task, I noticed that you're using the boxplot function instead of ggplot. There's not really a problem with that (I find myself using base graphics sometimes), but it's probably better to try to generate the plot using ggplot. It's good practice. On that note, you could use the "geom_boxplot" function to make the plots as well.
• With the second task, it may have been better to attempt a few other types of plots, rather than using the boxplots once again. I suggest using the boxplots in this task (since you are examining spread), but for the first task, maybe a bar graph or a time series would suffice to answer the question. Just for the sake of variety.
• Nice going in task three, presenting the data in two different ways. The second graph looks particularly informative. What seems to be missing though is the table to go along with this task. Perhaps the mean life expectancy for each continent of each year would be a good table?

Additional Remarks:

• Overall, good effort invested into the assignment. Would've liked to see maybe a few more tasks done, to sharpen your ggplot and dplyr skills.
  -Deprecation is when a function is no longer necessarily used, because it has been replaced by a different, newer function usually. This is done usually because the older function may not be efficient, or there may be other concerns with it, that the new function doesn't suffer from.

Overall Mark: Check

-Nikolas Krstic