Chapter 2

Summarizing Data

Learning Outcomes

• Use appropriate visualizations for different types of data (e.g. histogram, barplot, scatterplot, boxplot, etc.).
• Use different measures of center and spread and be able to describe the robustness of different statistics.
• Describe the shape of distributions vis-a-vis histograms and boxplots.
• Create and intepret contingency and frequency tables (one- and two-way tables).

Supplemental Readings

• OpenIntro Statistics slides
• ggplot2 - ggplot2 is an R package by Wickham that implements the grammer of graphics (Wilkinson, 2005) in R. I will frequently make use of the graphing framework throughout the course and is worth learning.
• Visualizing Likert Data - An R package for visualizing Likert scale data built on the ggplot2 framework.
• Quick-R base graphics - Covers many of the visualizations using R’s base graphics.

Videos

Summarizing and Graphing Numerical Data

Exploring Categorical Data

Note about Pie Charts

There is only one pie chart in OpenIntro Statistics (Diez, Barr, & ??etinkaya-Rundel, 2015, p. 48). Consider the following three pie charts that represent the preference of five different colors. Is there a difference between the three pie charts? This is probably a difficult to answer.

However, consider the bar plot below. Here, we cleary see there is a difference between the ratio of the three colors. As John Tukey famously said:

There is no data that can be displayed in a pie chart that cannot better be displayed in some other type of chart

Source: https://en.wikipedia.org/wiki/Pie_chart.