1. Displaying Distributions – Qualitative Variables
Lecture 14
Sections – 4.3.2
Tue, Feb 5, 2008

2. Pie Charts
Pie chart.
Use the percentage associated with the category to compute the central angle of the pie slice.
E.g., 25% of 360 = 90.
A pie chart facilitates the comparison of one category to the whole.

3. Racial Profiling by the Police?
Who gets pulled over.
Draw a pie chart of the data.

4. Who Gets Pulled Over
How does the distribution by race of those pulled over compare to the distribution in the general population?
Population
Pulled Over
White
73%
65%
Black
20%
24%
Hispanic 6% 7%

5. Who Gets Pulled Over The sample consisted of 520,079 cases.
If we compute the p-value, we get
p-value <
Is that significant?

6. Who Gets Pulled Over
An interesting question raised by the superintendent of the Virginia State Police:
“Do we know, at any given hour, what the demographics of I-95 in Richmond may be?”
What kind of bias (other than racial profiling) may be in play here?

7. Racial Profiling by Sharks?
Who gets bitten.

8. Bar Graphs
Bar graph.
A bar graph facilitates the comparison of one category to another.

9. Bar Graphs
Who get pulled over.
Draw a bar graph of the data.

10. Pie Chart Examples Where Your Income Tax Money Really Goes
Major Religions of the World Ranked by Number of Adherents
Warning against using piecharts