Research Methods

1. Research Methods Data Presentation

2. 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.

3. 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.

4. Figures or Charts • Pie Chart • Bar Chart (including Bilateral Bar Chart) • Histogram • Line Graph • Scatterplot • Any method to communicate [empirical] data through graphical means

5. Pie Chart

6. Bar Chart/Bar Graph

7. 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

8. Figures and Charts:Good Practices II • Legend • Comparison of two or more categorical variables only • Series or category not labeled elsewhere in the figure • Data 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

9. Bad Line Graph

10. Better Line Graph

11. Scatterplot

12. 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)

13. Transformed X and Scatterplot

14. Political Transformation and Scatterplot

15. Some Bad Practices for Figures or Charts I • Good practices (earlier) not satisfied • Tokens or acronyms where inappropriate (V0003059, LGINFR2, VAR3, X and Y) • Zero is not included on vertical axis • Using two-dimensional figures in place of bars or points (one-dimensional) • Comparing dissimilar groups on the same figure • Three-dimensions for one or two variables

16. 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 charts • Incorrect chart for the data (e.g. line chart for bar chart)

17. 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

18. Macropartisanship I

19. Macropartisanship II

20. Really Interesting Data Presentation I (Minard)

21. “I came to fight men, not Nature” - Napoleon http://www.stat.ucla.edu/history/march.htm

22. 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”.

23. Really Interesting Data Presentation II (Nightingale)

24. 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.

25. Figures for Distribution ofOne Variable

26. Figures for Relationship among Two (or More) Variables

27. Effective Tables • Title; Row and Column Headings; Data; Notes • Purpose 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 variable • Data sources • Definitions of important terms

28. Bad Practices:Tables TABLE II RMI turnout % 18 – 24 -.08 -.35 % Over 65 -.12 .09 % Bachelor’s degree -.21 -.08

29. Types of Tables • Univariate Table Descriptive Statistics Comparison of two distributions (such as sample and population) • Bivariate Table Crosstabulation Bivariate Statistics (Pearson correlation) • N-way Table Compare three or more variables