A course in quantitative research workflow for students in the higher education administration program at the University of Florida
Using the hsls_small.csv
data set and the online codebook, answer
the following questions. You do not need to save the final output
as a data file: just having the final result print to the console is
fine. For each question, I would like you to try to pipe all the
commands together. Throughout, you should account for missing values by
dropping them.
For each question, show your data work and, if necessary, answer the question in a short (1-2 sentence(s)) comment.
stu_id
x1stuedexpct
x1paredexpct
x4evratndclg
From this reduced data frame, reshape the data frame so that it is long in educational expectations, meaning that each observation should have two rows, one for each educational expectation type.
e.g. (your column names and values may be different)
stu_id | expect_type | expectation | x4evratndclg |
---|---|---|---|
0001 | x1stuedexpct | 6 | 1 |
0001 | x1paredexpct | 7 | 1 |
0002 | x1stuedexpct | 5 | 1 |
0002 | x1paredexpct | 5 | 1 |
<lastname>_assignment_4.R
) to our CANVAS
course site no later than 11:59 p.m. EDT on the due date.