A short description of the post.
Replace all the ???s. These are answers on your moodle quiz.
Run all the individual code chunks to make sure the answers in this file correspond with your quiz answers
After you check all your code chunks run then you can knit it. It won’t knit until the ??? are replaced
The quiz assumes you have watched the videos had worked through the exercises in exercises_slides-1-49.Rmd
Create a plot with the faithful dataset
add points with geom_point
assign the variable eruptions to the x-axis
assign the variable waiting to the y-axis
colour the points according to whether waiting is smaller or greater than 76
ggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting,
colour = waiting > 76))

faithful datasetgeom_point
eruptions to the x-axiswaiting to the y-axisggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
colour = "purple")

ggplot(faithful) +
geom_histogram(aes(x = waiting))

See how shapes and sizes of points can be specified here
Create a plot with the faithful dataset
add points with geom_point
eruptions to the x-axiswaiting to the y-axisggplot(faithful) +
geom_point(aes(x = eruptions, y = waiting),
shape = "triangle", size = 7, alpha =0.5)

faithful datasetgeom_histogram() to plot the distribution of the eruptions (time)ggplot(faithful) +
geom_histogram(aes(x = eruptions, fill = eruptions > 3.2))

mpg datasetgeom_bar() to create a bar chart of the variable manufacturerggplot(mpg) +
geom_bar(aes(x = manufacturer))

manufacturer instead of classmpg_counted <- mpg %>%
count(manufacturer, name = 'count')
ggplot(mpg_counted) +
geom_bar(aes(x = manufacturer, y = count), stat = 'identity')
ggsave(here::here("_posts/2021-03-28-exploratory-analysis/preview.png"))
manufacturer as a percent of totalclass to manufacturerggplot(mpg) +
geom_bar(aes(x = manufacturer, y = after_stat(100 * count / sum(count))))

For reference see examples.
Use stat_summary() to add a dot SEE QUIZ at the median of each group
color the dot purple
make the shape of the dot asterisk
make the dot size 7
ggplot(mpg) +
geom_jitter(aes(x = class, y = hwy), width = 0.2) +
stat_summary(aes(x = class, y = hwy), geom = "point",
fun = "median", color = "purple",
shape = "asterisk", size = 7 )
