Homework $2$: Due $9/13/24,11$:$59$pm

Instructions:

Place all work into a typed one$-$to$-$two page document. Upload both the document

and the CleanNLS.csv dataset created in Problem $2$e onto the Canvas homework page

by the due date. Documents must be in one of the following formats: $.$doc, $.$docx, or $.$pdf$.$

Data for completing these problems may be found under the "Files$/$Homework$/$Homework $2"$

page on Canvas.

The file NLS$2023.$csv contains data on a set of individuals. For each individual, the

following variables are measured: Urban $($whether or not the individual lives in an urban or

rural area$),$ Siblings $($number of siblings$),$ White $(1$ if the individual is white, $0$ otherwise$),$

Christian $(1$ if the individual is Christian, $0$ otherwise$),$ FamilySize, Height $($in inches$),$

Weight $($in pounds$),$ and Income.

Data Inspection:

$($a$)(1$pt$)$ How many observations are there in the dataset? How many variables are

there in the dataset?

$($b$)(1\mathrm{.}5$pt$)$ For each variable, how many missing entries are there? Also, give the

line or lines of $R$ code used to find this answer.

$($c$)(0\mathrm{.}5pt)$ Using the sort$()$ function, find the largest income for an individual in

the dataset. Find the smallest income for an individual in the dataset Also give

the line or lines of R code to find this answer.

Data Cleaning:

$($a$)(1$pt$)$ Remove all individuals from the dataset with $0$ income. Give the line or

lines of R code for this step.

$($b$)(1$pt$)$ Afterward, replace all missing incomes with the median of the non$-$missing

incomes. Give the line or lines of R code for this step.

$($c$)(1$pt$)$ Apply the log transformation $($either base $e$ or base $10)$ to the incomes and

add this as a column to the NLS$2023$ data frame. Give the line or lines of R code

to perform these steps.

$($d$)(1$pt$)$ Apply the square root transformation to weights and add this as a column

to the NLS data frame. Give the line or lines of R code to perform these steps.

$($e$)(1pt)$ Change the fourth entry of the Urban variable to your name. Give the line

or lines of R code to perform these steps.

$($f$)(2$pt$)$ After performing steps $2($a$),($b$),($c$),($d$),$ and $($e$),$ export this cleaned

dataset as a $.$csv file called CleanNLS.csv$.$ Give the line or lines of R code to

perform this step. Also, upload this file onto Canvas.