Organizing data
in tables and charts:
Criteria for effective presentation
Jane E. Miller, Ph.D.
Rutgers University
About the author
 Author: The Chicago Guide to Writing about
Multivariate Analysis (Chicago, 2005) and The
Chicago Guide to Writing about Numbers
(Chicago, 2004), and other articles about
statistical literacy and quantitative
communication.
 Professor, Rutgers University
 Institute for Health, Health Care Policy and Aging
Research.
 Edward J. Bloustein School of Planning and Public
Policy.
Learning objectives
To learn the different types of variables
and how they affect choices for organizing
data.
To become aware of different principles
for organizing variables in tables or charts.
To learn the strengths and weaknesses of
tables, charts, and prose for organizing
and conveying numeric information.
Performance objectives
To be able to choose among different
criteria for organizing data for a particular
task.
To be able to identify whether to use a
table or chart to present data for a specific
objective.
To understand how to write a prose
description to coordinate with a table or
chart.
Why does order of variables matter?
 The arrangement of items in a table or chart
should coordinate with order they are
mentioned in the prose description.

Avoid zigzagging back and forth across a chart or
among rows and columns of a table.
 Usually describe a pattern based on observed
numeric values, e.g., most to least common.
 Often a hypothesis includes some theoretical
basis of how items relate to one another.
Ordinal and continuous variables
 Values of ordinal, interval, and ratio variables
have an inherent numeric order.

E.g., age groups, dates, blood pressure.
 Numeric or chronological order of values is the
principle for organizing those values in a table
or chart.
Nominal variables
 Values of nominal variables have no inherent
numeric order.

E.g., categories of race, gender, or region.
 Need an organizing principle to determine
sequence of items.
 Same issue if you have >1 variable to present.
 Several
different causes of death.
 Prevalence of >1 symptoms, attitudes, etc.
+ and - of different tools
Strengths
Prose

Table



Chart



Easiest way to
explain patterns
Holds lots of #s
Good for detail
Predictable
structure
Holds lots of #s
Easy to see
general patterns
Predictable
structure
Weaknesses



Hard to organize a
lot of numbers
Harder to "see"
patterns
Difficult to see
specific values
Complementary use of
prose, tables & charts
Use tables and charts to present full
set of numeric values.
Use prose to describe the pattern or
address the hypothesis.
Use same ordering principle in table
or chart and its accompanying prose.
 Improves
clarity of narrative line.
Prose description of a pattern
Objectives:
 Describe
size and shape of the pattern.
 Explain whether it matches hypothesis.
Specify direction and magnitude of
association.
 Direction:
“Which is higher?
 Magnitude: “How much higher?”
Direction for different types of variables
Direction for ordinal, interval or ratio
variable:
 Is
the relationship positive, negative, or level?
 E.g., as income rises, do death rates
increase, decrease or remain constant?
For nominal variables:
 Which
category has the highest value?
 E.g., which gender has the higher death rate?
Principles for organizing data
Alphabetical order
Order of items on original data
collection instrument
Empirical order
Theoretical groupings
Arbitrary order – NEVER a good idea!
 Think
about how the data will be used,
and choose one of the above principles!
For tables and charts
accompanied by prose
Pattern description
or hypothesis testing
Example: Attitudes about legal abortion
“Please tell me whether or not you think it
should be possible for a pregnant woman
to obtain a legal abortion”
If the woman wants it for any reason
If there is a strong chance of defect in the baby
If the woman's own health is seriously
endangered by the pregnancy
If she is not married and does not want to marry
the man
If she becomes pregnant as a result of rape
If she is married and does not want any more
children
From the 2000 U.S. General Social Survey
% of
respondents
who agree
43.7
79.8
88.2
42.5
80.8
44.4
Order of items from questionnaire
% of respondents
Agreement with legal abortion under specified circumstances,
2000 U.S. General Social Survey
100
80
60
40
20
0
Any
reason
Defect in Wants no Mother's Pregnant
baby more kids health
due to
rape
Not
married
Order of items from questionnaire
% of respondents
Agreement with legal abortion under specified circumstances,
2000 U.S. General Social Survey
100
80
60
40
20
0
Any
reason
Defect in Wants no Mother's Pregnant
baby more kids health
due to
rape
Not
married
Alphabetical order
Agreement with legal abortion under specified circumstances,
2000 U.S. General Social Survey
% of respondents
100
80
60
40
20
0
Any
reason
Defect in Mother's
baby
health
Not
married
Rape
Wants no
more
Empirical order (descending)
Agreement with legal abortion under specified circumstances,
2000 U.S. General Social Survey
% of respondents
100
80
60
40
20
0
Mother's
health
Rape
Defect in Wants no
baby
more
Any
reason
Not
married
Theoretical grouping
Agreement with legal abortion under specified
circumstances, 2000 U.S. General Social Survey
% of respondents
100
80
60
40
20
0
Mother's Pregnant Defect in
health*
due to
baby*
rape*
Health reasons
Wants no
more
kids
Any
reason
Not
married
Social reasons
Theoretical grouping
Agreement with legal abortion under specified
circumstances, 2000 U.S. General Social Survey
% of respondents
100
80
60
40
20
0
Mother's Pregnant Defect in
health*
due to
baby*
rape*
Health reasons
Wants no
more
kids
Any
reason
Not
married
Social reasons
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Combining theoretical & empirical criteria
Descending dollar value of expenditures for
necessities and non-necessities,
2002 U.S. Consumer Expenditure Survey
$15,000
$12,000
$9,000
$6,000
$3,000
$-
Necessities
Non-necessities
Pattern with a third variable
% of respondents
Agreement with legal abortion, by gender of respondent and
circumstances of abortion, 2000 U.S. General Social Survey
Organized by topic of abortion question
100
Men
80
Women
60
40
20
0
Mother's Pregnant Defect in
health*
due to
baby*
rape*
Health reasons
Wants
Any
no more reason
kids
Not
married
Social reasons
* difference between men and women is statistically significant at p<.05
Pattern with a third variable
% of respondents
Agreement with legal abortion, by gender of respondent and
circumstances of abortion, 2000 U.S. General Social Survey
Organized by topic of abortion question
100
Men
80
Women
60
40
20
0
Mother's Pregnant Defect in
health*
due to
baby*
rape*
Health reasons
Wants
Any
no more reason
kids
Not
married
Social reasons
* difference between men and women is statistically significant at p<.05
Identifying theoretical criteria
Consult the published literature on
your topic to learn about theoretical
criteria for organizing your variables.
In new research areas, empirical
sorting may yield clusters with similar
response patterns that can then be
explored for conceptual overlap.
For self-guided data lookup
Why is it important? When is it used?
 Researchers
look up data for own
research questions, then organize the
data using empirical or theoretical
criteria.
How to organize data for such tasks?
 Alphabetical
order
 Order of items from data collection instrument
 Standard ordering used in periodic reports
Alphabetical order
Widely familiar principle, e.g., used in
Phone
book
Daily stock market report
Learned at an early age
Facilitates self-guided lookup
Ordering for a public data source
Order of items on original data
collection instrument
 Users
can refer to codebook
 Easy to find the variables they need
Ordering used in periodic reports
Standardized
topic
from year to year for a given
Summary
There is no one principle for
organizing numeric data that fits all
possible tasks.
Determine your main objective
 Hypothesis
testing or pattern description
 Data reporting for others’ use
Choose the organizing principle
accordingly.