We customized our box plot to make it more presentable. Let us review the customization options offered by the boxplot(...) function.

We used the boxplot(...) function's range argument to alter the length of each box's whiskers. In general, range will take on a positive value between 0 and 1.5. At 0, a box's whiskers will extend all the way to the most extreme data points. At a value greater than 0, the boxes' whiskers will reach data points within one interquartile range times the range value. An interquartile range is the distance between the top (third quartile) and bottom (first quartile) of a given box. This measure gives us an idea of how spread out the data are. By using a range value closer to 0, we are shortening our boxes' whiskers and excluding more extreme data points. On the other hand, a higher range value will include more extreme points and lengthen each box's whiskers. In our case, we used a range value of 1:

> boxPlotAllMethodsShuSoldiersRange <- 1

This shortened our whiskers by extending them to points no more than one interquartile range beyond their boxes. Note that we also revised our ylim argument to better display our boxes, given the new range:

> boxplot(formula = boxplotAllMethodsShuSoldiersData,
main = boxPlotAllMethodsShuSoldiersLabelMain,
xlab = boxPlotAllMethodsShuSoldiersLabelX,
ylab = boxPlotAllMethodsShuSoldiersLabelY,
ylim = boxPlotAllMethodsShuSoldiersLimY,
range = boxPlotAllMethodsShuSoldiersRange)

To further improve our plot's aesthetics, we revised its x-axis and y-axis labels. Before adding our own axes, we had to eliminate the default ones generated by R. This entailed giving the xaxt and yaxt arguments an n value:

> boxplotAllMethodsShuSoldiersAxtX = "n"
> boxplotAllMethodsShuSoldiersAxtY = "n"

Subsequently, we redrew our box plot without x-axis and y-axis:

> boxplot(formula = boxplotAllMethodsShuSoldiersData,
main = boxPlotAllMethodsShuSoldiersLabelMain,
xlab = boxPlotAllMethodsShuSoldiersLabelX,
ylab = boxPlotAllMethodsShuSoldiersLabelY,
ylim = boxPlotAllMethodsShuSoldiersLimY,
range = boxPlotAllMethodsShuSoldiersRange,
xaxt = boxplotAllMethodsShuSoldiersAxtX,
yaxt = boxplotAllMethodsShuSoldiersAxtY)

We then used the axis(...) function twice, once for the x-axis and once for y-axis, to customize our plot's axis labels. The axis(...) function accepts several optional arguments, a number of which were employed in the creation of our plot:

When executed, the axis(...) function draws a new axis atop the visual currently displayed in the graphic window. For instance:

> axis(side = 2, at = c(10, 20, 30), labels = c("a", "b", "c"),
las = 1)

The code would draw a new x-axis on the bottom of the chart with tick marks at 10, 20, and 30 paired with the labels a, b, and c, that have been oriented vertically. Similarly, we used the following code to customize our x and y axes:

> #custom x axis
> axis(side = 1, at = c(1, 2, 3, 4), labels = c("Ambush", "Fire",
"Head to Head", "Surround"), las = 0)
> #custom y axis
> axis(side = 2, at = c(1000, 25000, 50000, 75000, 100000),
las = 0)

Our custom x-axis was placed at the bottom of the plot and effectively renamed our four boxes to Ambush, Fire, Head to head, and Surround. Our custom y-axis was placed on the left side of the plot and incorporated more meaningful soldier values than were present in the default axis.

Create a box plot that depicts the relationship between the number of Wei soldiers targeted by each of the four battle methods. Be sure to customize your plot to improve its readability and emphasize its most important features.