The Chicago Guide to Writing about Multivariate Analysis, 2 nd edition. Creating effective tables and charts Jane E. Miller, PhD

The Chicago Guide to Writing about Multivariate Analysis, 2nd edition.The Chicago Guide to Writing about Multivariate Analysis, 2nd edition.

Creating effective tables and charts

Jane E. Miller, PhD


Overview

• Criteria for effective tables and charts• Guidelines for titles• Anatomy of a table• Anatomy of a chart• Examples• Practice writing sentences about table or chart


Criteria for an effective table or chart

• Self-contained• Succinct • Organized to coordinate with associated

narrative description


Review: Information needed to report a number

• W’s (context)– When– Where– What– Who

• Identity of each variable– No “alphabet soup” acronyms!– Meaningful words or phrases for each variable

• Units or categories for all variables shown


What does “self-contained” mean?

• Each table and chart in your work should be self-contained.

• Without reference to the text, readers should be able to understand:– Purpose of that particular table or chart– Context (W’s)– Variables– Units or categories for all variables– Acronyms or symbols

The Chicago Guide to Writing about Multivariate Analysis, 2nd edition.

Test of “self-contained”

• A reader unfamiliar with your data or study should be able to point to any number in the table and be able to write a complete, correct sentence about that number, based solely on the information in that table and its notes.

Population, number and percentage poor, by age group, United States, 2002

Age group (years)Number poor

(1,000s)Total population

(1,000s) % poor

<18 12,133 72,653 16.7

18–64 18,861 177,934 10.6

65+ 3,576 34,385 10.4

Total 34,570 284,972 12.1


What does “succinct” mean?

• Includes the information needed to address a specific question or set of related questions.

• Reduce clutter by avoiding– Unnecessary repetition of units within the table– Data labels on every point of the chart

• Remember: Charts are best for showing general level or shape, not precise values

– Excessive number of digits and decimal places• See chapter 4 of Writing about Numbers or Writing about

Multivariate Analysis.


Reducing duplicate labeling

• If every variable in the table is reported in dollars, don’t need to put “$” in every table cell– List the units in the title

• If an entire column is reported in percentage units, don’t need to put “%” in every cell.– List the units in the column label and convey “% of

what”


What does “well-organized” mean?

• Structure should be easy to follow based on conventions for labeling and reading.

• Coordinated with prose description of table or chart. Usually means– Theoretical criteria– Empirical criteria (ascending or descending order)– See podcast on organizing data in tables and charts


Writing an effective title• Pertain specifically to content of that table or

chart.– What question is that table/chart intended to answer?

• Include all “the W’s”– “What” is the topic of your table? Mention:

• Outcome (dependent) variables.• Predictor (independent) variables.

– “Who, when, where”?• If source name is too long, put it in a footnote.


Examples of titles• Poor: “Descriptive statistics”

– Way too general. Omits information about the topic, context, and types of statistics.

• Better: “Poverty patterns” – Identifies the dependent variable (poverty), but doesn’t convey

what patterns (comparisons) are presented.– Among who? When? Where?– What are the units for each of the variables reported in the table?

• Best: “Number and percentage poor by age group, United States, 2002”– Identifies dependent and independent variables, context ,and units.


TITLE: Name the “what”, “who”, “when,” where,” and “by” variables Column Spanner

Major row header Column header Column header Column header

Row header

Subgroup 1 Table cell Table cell Table cell

Subgroup 2 Table cell Table cell Table cell

Row header Table cell Table cell Table cell

Major row header

… Table cell Table cell Table cell

Anatomy of a table

*Footnote (i.e., source of data, definition of terms, acronyms)


Check: W’s: Who, what, when, where?

Check: Units or categories for all variables shown?

Note: “Poor”: family income below the federal poverty threshold for a family of given size and age composition.Source: Proctor and Dalaker. 2003. “Poverty in the United States: 2002.” Current Population Reports. P60–222. Washington, DC: US Government Printing Office.




(1,000s) % poor

<18 12,133 72,653 16.7

18–64 18,861 177,934 10.6

65+ 3,576 34,385 10.4

Total 34,570 284,972 12.1


Anatomy of a pie chart

• Composition of a categorical variable

• Categories are identified in the legend

• Units in the data labels• W’s in the title


Anatomy of a simple bar chart• Bivariate association between

– a categorical independent variable on the x-axis,

– a continuous dependent variable on the y-axis.

• Variables are identified on the axes, along with units (y-axis) or categories (x-axis).

• Note that categories are sorted in descending order of the value of the dependent variable, facilitating a well-organized written description.


Anatomy of a multiple-line chart• Three-way association

between one continuous and one categorical IV and a continuous DV.

• The dependent variable and its units are on the y-axis.

• The continuous IV and its units are on the x-axis.

• The categorical IV is labeled in the legend.


Range of values of independent variables

• Choose range of values for continuous independent variables that fit the topic and data.

• E.g., in model of birth weight:– Mother’s age at child’s birth plotted from 15 to 45 years

of age.• Corresponds with reproductive age range for women.

– Income/poverty ratio (IPR) plotted from 0.0 to 5.0.• Range that captures most of the observed values in the

data set used to estimate the model.


Writing sentences about aa table or chart

• Use title, labels, and footnotes to identify – The W’s– Units of measurement

• The contents of a specific table cell are identified by the labels on the pertinent rows and columns.

• The meaning of a specific point on a chart is identified by the pertinent axis labels and legend.





(1,000s) % poor

<18 12,133 72,653 16.7

18–64 18,861 177,934 10.6

65+ 3,576 34,385 10.4

Total 34,570 284,972 12.1

For the number in the green (underlined) cell, the row label (yellow) identifies the age group, the column label (blue) identifies the concept being measured and its units, and the table title identifies the W’s.

“There were more than 12 million poor children (<18 years) in the United States in 2002.”


Check: Self-contained pie chart?

• Write a sentence about the blue slice.• “In 2004, 16% of 4 year-olds in the US were obese.”• Check: Identify the

– category in the legend, – units in the data labels, – W’s in the title.


Check: Self-contained bar chart?• Describe transpiration under

the bright light condition.• “The bright light condition

resulted in the second highest rate of transpiration (5 ml/ m2/30 minutes). Only the fan (wind) condition yielded faster transpiration (8 ml/m2/30 minutes).”

• Check: – Concepts and units on the axes

and footnote– W’s in the title– Rank order (direction)


Summary

• Design your tables and charts to be– Self-contained– Succinct – Organized to coordinate with associated narrative

description

• Follow standard conventions for anatomy of tables and charts


Suggested resources• Chapters 4, 6, and 7 in Miller, J. E. 2004. The Chicago

Guide to Writing about NumbersOR• Chapters 4, 5, and 6 in Miller, J. E. 2013. The Chicago

Guide to Writing about Multivariate Analysis, 2nd Edition.

• Miller, J. E. 2007. “Organizing Data in Tables and Charts: Different Criteria for Different Tasks.” Teaching Statistics 29 (3): 98–101. – And related podcast


Suggested practice exercises• Study guide to The Chicago Guide to Writing about

Multivariate Analysis, 2nd Edition.– Problem sets for

• Chapter 5: questions 2, 5 and 7• Chapter 6: questions 2, 3, and 4

– Suggested course extensions for • Chapter 5

– “Reviewing” exercise #3– “Applying statistics” exercise #3– “Writing and revising” exercises #3 and 4

• Chapter 6– “Reviewing” exercises #1 and 2– “Applying statistics” exercises #1 and 2– “Writing and revising” exercise #3


Contact information

Jane E. Miller, [email protected]

Online materials available athttp://press.uchicago.edu/books/miller/multivariate/index.html

Documents

The Chicago Guide to Writing about Multivariate Analysis, 2 nd edition. Creating effective tables and charts Jane E. Miller, PhD