Exercise 3: Showing the data and customizing plots

Say we are interested in comparing gun homicide rates across regions of the US. We see this plot:

library(dplyr)
library(ggplot2)
library(dslabs)
data("murders")
murders %>% mutate(rate = total/population*100000) %>%
  group_by(region) %>%
  summarize(avg = mean(rate)) %>%
  mutate(region = factor(region)) %>%
  ggplot(aes(region, avg)) +
  geom_bar(stat="identity") +
  ylab("Murder Rate Average")

and decide to move to a state in the western region. What is the main problem with this interpretaion?

Possible Answers

The categories are ordered alphabetically.
The graph does not show standard errors.
It does not show all the data. We do not see the variability within a region and it's possible that the safest states are not in the West.
The Northeast has the lowest average.