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Research Methods. Data Presentation. Data Presentation: Figures and Tables. Consider your audience. The reader should understand (generally) the figure or table without reading the text. The reader should understand (generally) the text without looking at a figure or table. - PowerPoint PPT Presentation
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Data Presentation
Research Methods
Data Presentation:Figures and Tables
Consider your audience. The reader should understand (generally)
the figure or table without reading the text.The reader should understand (generally)
the text without looking at a figure or table.Text and figures and tables should be
coordinated—each improves the others. But, a picture (here, a figure or a table) is
worth a thousand words. More is communicated with figure or table than without.
Is Style Important for Communication?
Consider the following text example, without punctuation: A woman without her man is nothing.
With punctuation: A woman, without her man, is nothing.
Or, with punctuation: A woman: without her, man is nothing.
Figures or Charts
Pie ChartBar Chart (including Bilateral Bar Chart)HistogramLine GraphScatterplotAny method to communicate [empirical] data
through graphical means
Pie Chart
Percentage Use for Sources of Electricity, U.S. 2003
Coal51%
Nuclear21%
Natural Gas16%
Hydropow er6%
Petroleum3%
Other3%
Bar Chart/Bar Graph
Number of Hours of TV Watching on the Average DayGeneral Social Surveys, 2004
0.0
5.0
10.0
15.0
20.0
25.0
30.0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Hours of Television Viewing
Per
cen
t
Figures and Charts:Good Practices I
Title Identify topic and purpose of figure The research question or the relationships shown
in the chart Unique, distinguish between other related charts
Axis Titles and Labels Y-axis = Dependent Variable, X-axis =
Independent Variable Be precise, but minimize clutter
Figures and Charts:Good Practices II
Legend Comparison of two or more categorical variables
only Series or category not labeled elsewhere in the
figureData Labels
Use sparingly Identify reference points Report absolute level for pie or stacked bar chart If exact values necessary for reader, use a table
not a chart
Bad Line Graph
Figure 2
0.00
20.00
40.00
60.00
80.00
100.00
120.00
1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Better Line Graph
Figure 2Percentage of Collaboration for Research Articles,
By Journal and Decade
0
10
20
30
40
50
60
70
80
90
100
1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Decade (-4 to +5)
Per
cent
Coa
utho
red
AJP APSR JACS PR QRB
Scatterplot
Canadian Provincial Legislature Size by Population
0
20
40
60
80
100
120
140
0 2000000 4000000 6000000 8000000 10000000 12000000
Population
Leg
isla
ture
Siz
e
Several Weeks Ago…
Data Transformation Quantitative data may not be reported in a
manner that is most appropriate for theory a/o hypothesis to be tested
Should legislature size increase uniformly with population? No, say Taagepera (1972) and Stigler (1976)
Natural Logarithm of X values (population size)
Transformed X and Scatterplot
Canadian Provincial Legislature Size by Population (Logged)
0
20
40
60
80
100
120
140
10 11 12 13 14 15 16 17 18
Log(e) Population
Leg
isla
ture
Siz
e
Political Transformation and Scatterplot
Canadian Provincial Legislature Size by Population (Logged):With Ontario Change
Ontario (old)
0
20
40
60
80
100
120
140
10 11 12 13 14 15 16 17 18
Log(e) Population
Leg
isla
ture
Siz
e
Ontario (new)
Some Bad Practices for Figures or Charts I
Good practices (earlier) not satisfiedTokens or acronyms where inappropriate
(V0003059, LGINFR2, VAR3, X and Y)Zero is not included on vertical axisUsing two-dimensional figures in place of
bars or points (one-dimensional)Comparing dissimilar groups on the same
figureThree-dimensions for one or two variables
Some Bad Practices for Figures or Charts II
Enhanced features/colors/designs included that do not communicate the point of the figure
Inconsistent scale for a series of chartsIncorrect chart for the data (e.g. line chart
for bar chart)
An Example
Is partisanship stable or subject to short-term forces (such as the economy)?
Tradition view: individuals develop long-standing attachments to a political party
Result: Macropartisanship changes only at the margins
Challenge: Macropartisanship varies with “considerable magnitude” and varies systematically over time
Macropartisanship I
Erikson-McKuen-Stimson macropartisanhip measuresEMS Scaling
“Percent” is the Democratic share of party identif iers. Independents are deleted f rom the calculation.
19501952
19541956
19581960
19621964
19661968
19701972
19741976
19781980
19821984
19861988
19901992
19941996
19982000
20022004
200645
55
65
75Percent
Their series
Recent Gallup
GSS
Macropartisanship II
Erikson-McKuen-Stimson macropartisanhip measures
“Percent” is the Democratic share of party identif iers. Independents are deleted f rom the calculation.
19501952
19541956
19581960
19621964
19661968
19701972
19741976
19781980
19821984
19861988
19901992
19941996
19982000
20022004
20060
10
20
30
40
50
60
70
80
90
100Percent
Their seriesRecent Gallup
GSS
Really Interesting Data Presentation I (Minard)
http://www.stat.ucla.edu/history/march.htm
“I came to fight men, not Nature” - Napoleon
Minard
Probably the best statistical graphic ever drawn, this map by Charles Joseph Minard portrays the losses suffered by Napoleon's army in the Russian campaign of 1812.
Beginning at the Polish-Russian border, the thick band shows the size of the army at each position. The path of Napoleon's retreat from Moscow in the bitterly cold winter is depicted by the dark lower band, which is tied to temperature and time scales. Exquisitely printed in two colors on fine archival paper, 22” by 15”.
Really Interesting Data Presentation II (Nightingale)
Nightingale
Nightingale was a pioneer in the visual presentation of information. Among other things she used the pie chart, which had first been developed by William Playfair in 1801.
After the Crimean War, Nightingale used the polar area chart, equivalent to a modern circular histogram or rose diagram, to illustrate seasonal sources of patient mortality in the military field hospital she managed.
Nightingale called a compilation of such diagrams a "coxcomb", but later that term has frequently been used for the individual diagrams.
She made extensive use of coxcombs to present reports on the nature and magnitude of the conditions of medical care in the Crimean War to Members of Parliament and civil servants who would have been unlikely to read or understand traditional statistical reports.
Figures for Distribution ofOne Variable
Task Type of Figure Comments Nominal, few
categories (≤ 5)
Pie chart Arrange categories by frequency or theoretical criteria
Nominal, many categories (> 5)
Bar chart Arrange categories by theoretical criteria or frequency
Ordinal
Bar chart or histogram
Arrange categories in order
Continuous, with few (< 20) values
Histogram Arrange values in numeric order
Continuous, with many (≥ 20) values
Line graph Arrange values in numeric order
Figures for Relationship among Two (or More)
Variables
Task Type of Figure Comments
Both categorical Bar chart Bar height to show percentage or frequency of each variables
Clustered bar chart, or clustered histogram
Within each category, create a frequency for each group
Stacked bar chart Within each category, group of second variable stacked in a single bar
One categorical, one continuous
Bar chart Categorical variable on x-axis, continuous variable on y-axis
Both continuous Line graph Trend; one Y for each X, dependent variable on Y-axis, independent variable on X-axis
Scatterplot Individual points that are not linked, more than one Y for an X, DV on Y-axis, IV on X-axis
Effective Tables
Title; Row and Column Headings; Data; NotesPurpose of the table (title)Context of the table (title, notes)Location of specific variables in the table
(headings)Coding or units of measurement for each
variableData sourcesDefinitions of important terms
Bad Practices:Tables
TABLE II
RMI turnout% 18 – 24 -.08 -.35% Over 65 -.12 .09% Bachelor’s degree
-.21 -.08
Types of Tables
Univariate TableDescriptive StatisticsComparison of two distributions (such as sample and population)
Bivariate TableCrosstabulationBivariate Statistics (Pearson correlation)
N-way TableCompare three or more variables
Table 7 Transferable and Nontransferable Votes by Count/Round
1997 Irish General Election
Count Number of Districts Transferred Votes
Nontransferable Vote
Percent Nontransferable
2nd 41 59583 1773 2.98 % 3rd 41 50194 2931 5.84 4th 39 77936 7959 10.21 5th 37 81391 9062 11.13 6th 31 65244 6016 9.22 7th 29 99272 12744 12.84 8th 22 57461 9664 16.82 9th 16 37151 7041 18.95
10th 11 29068 6474 22.27 11th 7 20058 6039 30.11 12th 2 2491 388 15.58 13th 1 2457 298 12.13 14th 1 2574 729 28.32 15th 1 5659 507 8.96
TOTAL 41 590539 71625 12.13 % Transferable votes are ballots for which the preference is transferred to the next, ordered available candidate.