Question $3$

Create a graphic of mean weight of the child versus year, which includes separate lines for the two top race categories, white and black, coded as $1$ and $2,$ respectively. The graphic should look like the following. Notice that the legend is different from the default legend. You'll want to investigate scale$\_$color$\_$discrete This section will use the $`$BirthDataWithRegionColors$.$csv$`$ data set. This contains data about births in the United States, collected by the Centers for Disease Control $($CDC$).$ The variables in the data$-$set a is subset of the variables in the full data set, and the observations represent a "small" sample $($chosen at random$)$ of slightly over one million record

Variable $|$ Description

$---------|------------$

$`$year$`|$ the year of the birth

$`$month$`|$ the month of the birth

$`$state$`|$ the state where the birth occurred, including $"$DC$"$ for Washington D$.$C$.$

$`$is$\_$male$`|$ which is $`$TRUE$`$ if the child is male, $`$FALSE$`$ otherwise

$`$weight$\_$pounds$`|$ the child's birth weight in pounds

$`$mother$\_$age$`|$ the age of the mother

$`$child$\_$race$`|$ race of the child.

$`$plurality$`|$ the number of children born as a result of the pregnancy, with $1$ representing a single birth, $2$ representing twins, etc.

Combine $`$dplyr$`$with $`$ggplot$2`$ to create graphical displays of the data. Use $`$filter$`,`$group$\_$by$`,$ and $`$summarize$`$ to build the required data frame.

WHAT TO FIND:

Create a graphic of mean weight of the child versus year, which includes separate lines for the two top race categories, white and black, coded as $1$ and $2,$ respectively.

year month state is$\_$male weight$\_$pounds mother$\_$age child$\_$race plurality region state$\_$color

$19692$ CA TRUE $6\mathrm{.}999676819201$ NA West blue

$19693$ CA FALSE $6\mathrm{.}876217952252$ NA West blue

$19695$ CA TRUE $7\mathrm{.}187069741301$ NA West blue

$19695$ CA FALSE $7\mathrm{.}749248509171$ NA West blue

$19695$ CA TRUE $7\mathrm{.}374462664224$ NA West blue

$19696$ CA TRUE $9\mathrm{.}625382359262$ NA West blue

$19698$ CA FALSE $7\mathrm{.}936641432261$ NA West blue

$19698$ CA FALSE $6\mathrm{.}499227484191$ NA West blue

$196911$ CA FALSE $9\mathrm{.}063203591251$ NA West blue

$196911$ CA FALSE $7\mathrm{.}625789643262$ NA West blue

$196911$ CA FALSE $7\mathrm{.}687519076261$ NA West blue

$19693$ CT FALSE $6\mathrm{.}311834561311$ NA Northeast blue

$19693$ CT TRUE $6\mathrm{.}250105128281$ NA Northeast blue

$19696$ CT TRUE $7\mathrm{.}813182565241$ NA Northeast blue

$19697$ CT TRUE $6\mathrm{.}686620406201$ NA Northeast blue

$196910$ CT TRUE $8\mathrm{.}187968411231$ NA Northeast blue

$19693$ DC FALSE $7\mathrm{.}561855587231$ NA South blue

$19698$ DC FALSE $6\mathrm{.}375768617192$ NA South blue

$196911$ DC FALSE $6\mathrm{.}999676819212$ NA South blue

$196911$ DC FALSE $7\mathrm{.}687519076222$ NA South blue

$19691$ IL TRUE $7\mathrm{.}500126153251$ NA Midwest blue

$19696$ IL FALSE $6\mathrm{.}499227484301$ NA Midwest blue

$19695$ IL TRUE $8\mathrm{.}811876612242$ NA Midwest blue

$19697$ IL FALSE $4\mathrm{.}812691179182$ NA Midwest blue

$19697$ IL FALSE $7\mathrm{.}561855587271$ NA Midwest blue

$196912$ IL TRUE $7\mathrm{.}125340308261$ NA Midwest blue

$19691$ IL FALSE $8\mathrm{.}688417745211$ NA Midwest blue

$19698$ IL FALSE $8\mathrm{.}000575488301$ NA Midwest blue

$19692$ MD FALSE $7\mathrm{.}125340308252$ NA South blue

$19699$ MD FALSE $1\mathrm{.}062628103261$ NA South blue

$19691$ MA TRUE $5\mathrm{.}875319282241$ NA Northeast blue