1- Load the R package we will use.

library(tidyverse)

Quiz questions

• Replace all ???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

Pick one of your plots to save it as preview plot. Use the ggsave command at the end of tyhe chunk of the plot that you want to preview

Question: modify slide 34

• Create a plot with 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 77

ggplot(faithful) +
  geom_point(aes(x = eruptions, y = waiting,
                 colour = waiting > 77))

Question: modify intro-slide 35

• Create a plot with the faithful dataset • add points with geom_point * assign the variable eruptions to the x-axis * assign varibale waiting to the y-axis * assign the colour purple to all points

ggplot(faithful) +
  geom_point(aes(x = eruptions, y = waiting),
             colour = "purple")

Question: modify intro-slide 36

• Create a plot with the faithful dataset • use geom_histogram() to plot the distribution of waiting time * assign the variable waiting to the x-axis

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

Question: modify geom-ex-1

• See how shapes and sizes of points can be specified here: https://ggplot2.tidyverse.org/articles/ggplot2-specs.html#sec:shape-spec • 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 set the shape of the points to cross set the point size to 4 set the point transparency 0.3

ggplot(faithful) +
  geom_point(aes(x = eruptions, y = waiting),
             shape = "cross", size = 4, alpha = 0.3)

Question: modify geom-ex-2

• Create a plot with the faithful dataset • use geom_histogram() to plot the distribution of the eruptions (time) • fill in the histogram based on whether eruptions are greater than or less than 3.2 minutes

ggplot(faithful) +
  geom_histogram(aes(x = eruptions, fill = eruptions > 3.2))

Question: modify stat-slide-40

• Create a plot with the mpg dataset • add geom_bar() to create a bar chart of the variable manufacturer

ggplot(mpg) + 
  geom_bar(aes(x = manufacturer))

Question: modify stat-slide-41

• change code to count and to plot the variable manufacturer instead of class

mpg_counted <- mpg %>% 
  count(manufacturer, name = "count")
ggplot(mpg_counted) + 
  geom_bar(aes(x = manufacturer, y = count), stat = "identity")

Question: modify stat-slide-43

• change code to plot bar chart of each manufacturer as a percent of total • change class to manufacturer

ggplot(mpg) +
  geom_bar(aes(x = manufacturer, y = after_stat(100*count / sum(count))))

Question: modify answer to stat-ex-2

for reference see: https://ggplot2.tidyverse.org/reference/stat_summary.html?q=stat%20_%20summary#examples

• Use stat_summary() to add a dot at the median of each group • color the dot blueviolet • make the shape of the dot cross • make the dot size 9

ggplot(mpg) +
  geom_jitter(aes(x = class, y = hwy), width = 0.2) +
  stat_summary(aes(x= class, y = hwy), geom = "point",
               fun = "median", color = "blueviolet", 
               shape = "cross", size = 9)

ggsave(filename = "preview.png",
       path = here::here("_posts", "2022-03-14-explanatory-analysis"))

Explanatory analysis