In jrminter/statshelpR: Convenience functions for statistical analysis

knitr::opts_chunk$set(echo = TRUE, warning=FALSE)
suppressWarnings(suppressMessages(suppressPackageStartupMessages(library(ggplot2))))

Introduction

Dotplots were made popular by the statistician W. S. Cleveland and are described in the book The Elements of Graphing Data.

The R core team implemented this function in the base graphics package as the function stripchart. You can get help on this function by typing the command ??stripchart.

There is a helpful YouTube video here.

Example

Introduction

This example is used data supplied from page 41 in your text Robert Johnson and Patricia Kuby.

Analysis

Input the data

Use the list of 19 exam grades from Illustration 2.3 on p. 41. We will create a list named grades.

grades <- c(76, 74, 82, 96, 66, 76, 78, 72, 52, 68,
            86, 84, 62, 76, 78, 92, 82, 74, 88)

Make the dotplot

First, use the base graphics function stripchart:

stripchart(grades, method="stack", at=c(0.05), pch=20, cex=3, las-1,
           frame.plot=FALSE, xlim=c(50,100), main="Exam grades")

We can also try the newer ggplot2 graphics.

df <- data.frame(grades=grades)
a <-  ggplot(df, aes(x = grades)) +
      geom_dotplot(binwidth=1) +
      scale_x_continuous(breaks=seq(from=50, to=100, by=5),
                         limits = c(50, 100)) +
      scale_y_continuous(NULL, breaks = NULL) +
      xlab("grade") +
      theme(axis.text=element_text(size=12),
            axis.title=element_text(size=12),
            plot.title=element_text(hjust = 0.5))
print(a)

For comparison, let's look at the histogram using the base graphics function. We will set the breaks to have bins one grade wide. In general, histograms are more useful, especially for larger data sets.

minG <- min(grades)-1
maxG <- max(grades)+1
breaks <- seq(minG, maxG, 1)
a <- hist(grades, breaks, xlim=c(minG, 100))

Now try the newer ggplot2 approach

a <- ggplot(df, aes(x = grades)) +
     geom_histogram(bins=50) +
     xlab("grade") + 
     ggtitle("Exam grade distribution") +
     theme(axis.text=element_text(size=12),
           axis.title=element_text(size=12),
           plot.title=element_text(hjust = 0.5)) # center the title
print(a)