As explained in the syllabus, the exam consists of two components.
The first is a take-home exam that will be distributed by noon on
Monday, November 14th. To access the exam, you will run the
notebook00.Rmd file; that will download the file
exam03.Rmd, which contains the exam questions, and any
associated datasets. Answer the questions as you have done in the class
notebooks, knit the notebook, and bring your printed solutions to class
on Wednesday, November 16th. You may use any static resources for the
exam but cannot discuss the questions with anyone else.
The dataset for the exam has a spatial component and a temporal component. The temporal information is given as a date; there are no questions related to datetimes, times, or timezones. The questions will most closely resemble Notebooks 17-20. Pay close attention to the code formating rules in the first and second set of notes. You will lose points for formatting errors on the take-home exam.
The in-class exam will take place on October 16th. It is a closed book exam that will be done entirely on paper. There will be ten questions. It will be closer to the first exam, requiring you to be able to hand-write some R code. The questions, however, will generally be less involved than those on the take-home exam.
For the in-class exam, I will be asking you to work with the same dataset from the take-home portion of the exam. Similar to the second exam, I will give you a sheet of paper that shows the first few rows, names, and column types of the three tables. I will ask you 10 questions that are similar in style of the easier questions on the notebooks.
I don’t expect you to have memorized all of the functions we have
used this semester. Even after using R for the past 15+ years, with the
more involved functions or those I only use occasionally (such as
pivot_longer or the various scale functions), I often need
to quickly look at the help pages to remember all of the options. For
this exam, you will only need to be able to use the following
functions:
ggplot(),
aes(), geom_point(),
geom_text_repel(), geom_line()filter(),
mutate, slice(), arrange(),
desc(), group_by(),
summarize(),left_join() (you’ll
need to use the “by” argument, but nothing else)year(),
month(), day() (no need to use any of the
options for month)spatial_join(),
geom_sf()fct_inorder(),
if_else(), mean(), n()
>=, <=, >,
<, %>%Each question should require at most four data verbs to complete.