 # Load the 2017NBADraft2.txt data set into R. a Create a histogram (...

## Question

a Create a histogram (with appropriate title) on the Height variable.
b Create a multiple boxplot (with appropriate title) comparing height between the diﬀerent positions. c Create a scatter plot with height on the x-axis and wingspan on the y-axis.
d Create a scatter plot with a ﬁtted loess curve for height (x-axis) and weight (y-axis).
e Create a scatter plot matrix using the four numeric variables in the data set (including birthdate).

Load the DuckSurvival2.txt data set into R.
a Create a histogram (with appropriate title) for wing length. Report the output.
b Create a multiple boxplot (with appropriate title) comparing wing length between ducks with
diﬀerent statuses. Report the output.
c Which status group has the largest median? How can you tell based on the boxplots?
d Create a scatter plot matrix comparing the survival time, body weight, and wing length (and only those variables) to each other. Report the output.

## Solution Preview

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library(ggplot2)

g <- ggplot(dat, aes(x = Height))
g + geom_histogram() + xlab("Height") + ylab("Count") + ggtitle("Histogram of Draft's Height")

g <- ggplot(dat, aes(x = Position, y = Height))
g + geom_boxplot() + ggtitle("Boxplot of Height for each Position") + xlab("Position") + ylab("Height")

g <- ggplot(dat, aes(x = Height, y = Wingspan))
g + geom_point() + xlab("Height") + ylab("Wingspan") + ggtitle("Scatter plot of Height and Wingspan")

g <- ggplot(dat, aes(x = Height, y = Weight))
g + geom_point() + xlab("Height") + geom_smooth(method = "loess") + ylab("Weight") + ggtitle("Scatter plot of Height and Weight with loess curve")...

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