Bar Chart, or Bar Plot or Bar Graph

- This is a Plot that can be useful for Exploratory Data Analysis
- It's a graphical representation of Frequency Tables
- It shows the values of your data set with bars
- height of the bar is proportional to the value it represents
- so the variables you plot must be Quantitative Variables

To create a bar chart in R

- use
`barplot`

command

r = dnorm(seq(from=-3, to=3, length=15), mean=0, sd=1) barplot(r, col="red")

Bar Charts can also be used for comparing values of two and more variables

- typically, they are graphical representation of Contingency Tables

There are the following types of bar charts:

- Side-by-side bar chart
- bars are put near each other

- Stacked (Segmented) bar chart
- shows more information than other types - the total size, the proportion, etc

- Proportional stacked bar chart
- standardized version of the stacked bar chart
- makes it easier to see the Joint Distribution of variables

In R

library(openintro) data(email) # stacked t = table(email$spam, email$number) pal = c('yellow2', 'skyblue2') barplot(t, col=pal, beside=F) # proportional t.prop = rbind(t[1,] / colSums(t), t[2,] / colSums(t)) pal = c('yellow2', 'skyblue2') barplot(t.prop, col=pal, beside=F) # side-by-side barplot(t, col=pal, beside=T)

They can represent the information about the distribution better than proportional bar charts

- they use areas to represent the distribution
- e.g.