代写R语言小作业，完成四个问题。
Instructions
When you have completed the assignment, knit the document into a PDF file, and
upload both the .pdf and .Rmd files to Canvas.
Note that you must have LaTeX installed in order to knit the equations below.
If you do not have it installed, simply delete the questions below.
Question 1
In this assignment, you will be required to find a set of data to run
regression on. This data set should be financial in nature, and of a type that
will work with the models we have discussed this semester (hint: we didn’t
look at time series) You may not use any of the data sets in the ISLR package
that we have been looking at all semester. Your data set that you choose
should have both qualitative and quantitative variables. (or has variables
that you can transform)
Provide a description of the data below, where you obtained it, what the
variable names are and what it is describing.
Question 2
Pick a quantitative variable and fit at least four different models in order
to predict that variable using the other predictors. Determine which of the
models is the best fit. You will need to provide strong reason why the
particular model you chose is the best one. You will need to confirm the model
you have selected provides the best fit and that you have obtained the best
version of that particular model (i.e. subset selection or validation for
example). You need to convince the grader that you have chosen the best model.
Question 3
Do the same approach as in question 2, but this time for a qualitative
variable.
Question 4
For the Boston data set, fit a tree trying to predict crime (crim) based on
all of the other variables. This should be the best tree that you can fit (you
should try bumping, bagging, and boosting to ensure this).
