Chapter 10
STA 200 Summer I 2011
Data Tables
• One way to organize data is to create a data
table.
• Good data tables have:
– a clear heading
– clearly labeled variables
– rates instead of (or supplemental to) counts
Example
1912 Presidential Election:
Candidate
Party
Number of
Votes
Percentage
W. Wilson
Democratic
6,296,284
41.8%
T. Roosevelt
Progressive
4,122,721
27.4%
W. H. Taft
Republican
3,486,242
23.2%
E. V. Debs
Socialist
901,551
6.0%
Other
242,036
1.6%
Total
15,048,834
100.0%
Data Tables (cont.)
• A data table shows:
– what values a variable takes
– how often it takes those values
• In other words, a data table shows the
distribution of a variable.
Types of Variables
• Some variables place individuals into categories
(gender, eye color, state of residence), while
others have a meaningful numerical scale
(distance, height, exam score).
• A variable that places individuals into categories
is called a categorical variable.
• A variable with a meaningful numerical scale is
called a quantitative variable.
Graphing Categorical Variables
• Categorical variables can be graphed using a
pie chart or a bar graph.
• Thus, we could graph the presidential election
data using either a pie chart or bar graph.
• When constructing a bar graph, make sure the
bars don’t touch.
Example (Pie Chart)
Percentage of Votes
Debs, 6%
Other, 1.60%
Taft, 23.20%
Roosevelt,
27.40%
Wilson, 41.80%
Example (Bar Graph)
Percentage of Votes
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Wilson
Roosevelt
Taft
Debs
Other
or…
Number of Votes
7,000,000
6,000,000
5,000,000
4,000,000
3,000,000
2,000,000
1,000,000
0
Wilson
Roosevelt
Taft
Debs
Other
Bad Graphs (Pictogram)
Pictograms
• A pictogram is another way to graphically
display a categorical variable.
• Pictograms can be misleading, since the
difference between two values is often poorly
represented.
Bad Graphs (Clutter)
Line Graphs
• Line graphs are used to display change over
time.
• When constructing a line graph, always put
time on the horizontal axis and the variable on
the vertical axis.
Example
Line Graphs (cont.)
• Things to look for:
– patterns/trends
– deviations
– seasonal variation
• Seasonal variation occurs if a pattern in a
graph repeats over regular time intervals.
Example (Seasonal Variation)
Misrepresenting Data
• It’s easy for data to be misrepresented in a
line graph.
• Depending on how the axes are calibrated,
change over time can look more severe or less
severe than it should.
Example (Misrepresenting Data)
Example (cont.)