# Lab 2 Solutions

## Exercise 1

All six of these plots map the same variables to the `x` and `y` aesthetics.

``````p <- ggplot(mpg, aes(x=displ, y=hwy))
``````

We can now add to the object `p` the appropriate geoms to create the six plots.

``````p + geom_point() + geom_smooth(method='loess', se=F) # the x and y aesthetics are already mapped
p + geom_point() + geom_smooth(aes(group=drv), se=F)
p + geom_point(aes(color=drv)) + geom_smooth(aes(color=drv),se=F)
p + geom_point(aes(color=drv)) + geom_smooth(se=F)
p + geom_point(aes(color=drv)) + geom_smooth(aes(linetype=drv), se=F)
# the white points appear "under" the multicolor points
p + geom_point(color='white', size=4) + geom_point(aes(color=drv), size=1.5)
``````

## Exercise 2

You can use either `geom_point` or `geom_jitter` to plot the points.

``````ggplot(ChickWeight) +
geom_point(aes(x=Time, y=weight, color=Diet), shape=1,
position=position_jitter(width=0.25, height=0))+
stat_summary(aes(x=Time,y=weight,color=Diet),
geom='line',fun.y=mean) +
scale_color_hue(name='Mean weight',
breaks=1:4,
labels=c("Diet 1","Diet 2","Diet 3","Diet 4"))
``````
``````ggplot(ChickWeight) +
geom_jitter(aes(x=Time, y=weight, color=Diet),
width=0.25, height=0, shape=1) +
stat_summary(aes(x=Time, y=weight, color=Diet), geom='line', fun.y=mean) +
scale_color_hue(name='Mean weight',
breaks=1:4, labels=c("Diet 1","Diet 2","Diet 3","Diet 4"))
``````