To help you select a good chart, use the chart selector guide in Figure 7.1 . This diagram helps you think about which kinds of chart to consider, depending on what you want your data to demonstrate. Your choice of chart will depend fi rst on what task you want the chart to accomplish on the slide. Each chart could accomplish any of four tasks on a slide:
it can show a relationship (e.g., when advertising goes up, sales go up too); it can make a comparison (e.g., retention rates are higher among women than among men, or this year ’ s sales are higher than last year ’ s); it can display the distribution of your data (e.g., there is a broad range of prices that people are willing to pay for car warranties); and it can show the composition of your data — what the component parts are (e.g., fi nal cost of the product is made up of manufacturing cost, transportation cost, and insurance).
Next, you must consider various characteristics of your data set, such as the number of observations, the number of variables per observation, and whether you are looking at static (point - in - time) data or data over time (time series). Which characteristics will drive your choice of chart depends on your initial choice of what you are intending to demonstrate.
The way to use this diagram is as follows. Start in the middle, with the question “ What would you like to show? ” Then decide which of the four choices you want your data to demonstrate: relationship, comparison, distribution, or composition. If you want to show more than one of these, you will probably end up drawing more than one chart.
Displaying Relationships Within Data
If you want to show that your data provides evidence of a relationship, for example, between advertising and sales revenues, then you would move to the bottom of Figure 7.1 . 2 See Mayer (2001). Also, recall is
lower, and likelihood of distraction higher (Edell & Staelin, 1983).
This is known as the coherence principle: “ Students learn better when extraneous material is excluded rather than included in a lesson ” (Moreno, 2006, p. 65, building on Mayer, 2001).
2 See Mayer (2001). Also, recall is lower, and likelihood of distraction higher (Edell & Staelin, 1983).
This is known as the coherence principle: “ Students learn better when extraneous material is excluded rather than included in a lesson ” (Moreno, 2006, p. 65, building on Mayer, 2001).
3 See Feinberg & Murphy (2000).
In two related studies, students performed worse on quizzes and recall and recognition tasks when irrelevant pictures were used in presentations (Bartsch & Cobern, 2003). In an eye - tracking test, students eyes were drawn more to relevant photographs on PowerPoint slides than to irrelevant ones (Slykhuis, 2005).
3 See Feinberg & Murphy (2000).
In two related studies, students performed worse on quizzes and recall and recognition tasks when irrelevant pictures were used in presentations (Bartsch & Cobern, 2003). In an eye - tracking test, students eyes were drawn more to relevant photographs on PowerPoint slides than to irrelevant ones (Slykhuis, 2005).
4A study by Bergen, Grimes, &
Potter (2005) showed that audiences recalled about 10 percent fewer facts from news stories communicated in a format in which graphical clutter is added to the video of the announcer than from news stories without the visual clutter.
4A study by Bergen, Grimes, &
Potter (2005) showed that audiences recalled about 10 percent fewer facts from news stories communicated in a format in which graphical clutter is added to the video of the announcer than from news stories without the visual clutter.
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VISUAL PRESENTATION ELEMENTS: GRAPHICS, CHARTS, COLOR, ANIMATION, AND FONTS 99
FIGURE 7.1. Chart Selector Guide
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When choosing the right chart for displaying a relationship, the important characteristic is the number of variables in your data; for bivariate data, a scatter plot is appropriate, while for trivariate data, a bubble chart works well. The relationship between advertising and unit sales involves two variables (advertising and unit sales), and therefore a scatter plot would be a good choice here.
If you wanted to show the relationship of advertising, price, and unit sales (three vari- ables), then the suggestion is a bubble chart, where the x - axis, the y - axis, and the size of the bubbles represent the three variables.
Displaying Data Distribution
If you want to show the distribution of your data, move to the top of Figure 7.1. If you have univariate data, move upward and left. If your observations are graphed into few intervals, the suggested chart is a column histogram; if many intervals, a line histogram. For example, if you are showing age breakdown of a particular sample of people in brackets of twenty years (0 to 19, 20 to 39, 40 to 59, etc., that is, few intervals), then a column histogram would be appropriate. If you are showing instead age breakdown by year (how many people are age 0, 1, 2, 3, etc., that is, many intervals) then a line histogram is suggested. To the right of that, if you have bivariate data, a scatter chart is proposed, and if trivariate data, a 3D area chart.
Displaying Comparisons
To show a comparison, move to the left of the fi gure. The fi rst question is whether you want to show how your data is changing over time, in which case follow the chart to the upper left, or if it is static data, just a single period, which is at the lower left. For static data, use a bar chart for univariate data, with each bar representing one observation.
Sales for fi ve different companies would be shown on fi ve different bars. Bar charts (bars lie horizontally) are for comparisons among things, while column charts (columns rise vertically) are for comparisons over time.
For static bivariate data, use a variable width column chart. The height of each column corresponds to one variable, and the width, the other. So if you had two variables repre- senting sales — dollar sales and sales growth — each column would be drawn using those two variables. (Although drawing this chart in column form would seem to contradict the conclusion that columns are only for showing change over time, I have never seen it drawn in bar form.) For static multivariate data with few subjects, use multiple bar charts, lined up across the page, where each chart represents one subject and each of the bars correspond to the different variables. For example, if you wanted to compare GDP per capita, GPD growth, population size, population growth, and population density (vari- ables) for four different countries (subjects), then each of the bar charts would represent one country, while each of the bars would represent one of the variables for that country.
This way you can compare variables across subjects by reading across the page, and vari- ables within each subject by looking at each bar chart as a whole.
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VISUAL PRESENTATION ELEMENTS: GRAPHICS, CHARTS, COLOR, ANIMATION, AND FONTS 101
Finally, where you have many items and many variables, use a trellis chart, which is a table of charts. You can either use the table as a space saver — allowing you to fi t, say, twenty bar charts on a page in a four - by - fi ve matrix — or you can use it to highlight one or two of the more important variables by using those variables to determine which cell in the table you place each chart on. (Of course, there are limits to this approach, because you cannot place more then one chart in each cell, and the intervals on each axis have to be roughly equal.)
For time - series data, if you have only a few periods of data, then you could use a column chart if you also have only a few data items (with each data item represented by a differ- ent set of columns, in different colors or shades of gray), or else a line chart if you have many data items, with several lines, one for each data item.
If you have many periods of data, then also use a line chart if you have non - cyclical data or a circular area chart (sometimes called a spider chart) for cyclical data.
Composition of Data
The last option, on the right side of Figure 7.1, is composition: this is when you want to highlight the components of your data. Your fi rst choice here is again whether your data is static or changing over time. Time - series data is also a comparison of sorts — except that you are comparing the same items over time, rather than different items — so the options are similar to the choices for comparisons. If you have few time periods to dis- play, then choose a stacked column chart to show both the relative and absolute differ- ences between periods, and if only the relative differences matter, than use a stacked 100 percent column chart, where the height of each column is fi xed and the components are shown as percentages rather than absolute numbers.
If you have many periods to show, then you will again use lines rather than columns. To show relative and absolute differences over time, use a stacked area chart, and to show relative differences only, use a stacked 100 percent area chart. Options for displaying static data are at the upper right. For showing a simple share of total, the pie chart is very popular, although some people have found it to be less effective than other options. If you are trying to show how components of your data add up to and subtract from a total, use a waterfall chart, and if you want to show how some of your subcomponents also have sub- components, then a stacked 100 percent column chart with subcomponents is ideal.
The chart selector diagram is only a guide. The best way to decide which chart to use, once you have decided what you want to show with your data, is to use the diagram for suggestions and then try a few alternatives — have your colleagues take a look at the options — to see which one works best. 5
Fortunately, one factor that does not seem to be important in choosing a good chart is audience personality type, so while audience personality type is critical for several other aspects of your presentation design (see Chapter 1 ), it does not appear to be relevant to choosing charts. 6
5 An experimental electronic version of the chart selector diagram is available at www.ChartChooser.com . 5 An experimental electronic version of the chart selector diagram is available at www.ChartChooser.com .
6 Research on impact of different graph types on personality types didn ’ t fi nd any signifi cant differences (So & Smith, 2003).
6 Research on impact of different graph types on personality types didn ’ t fi nd any signifi cant differences (So & Smith, 2003).
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As you consider which charts to use, make sure that you include lots of relevant detail:
detail improves the persuasiveness of your presentation. (Chapter 8 will discuss the importance of adding lots of detail — properly organized – to each of your slides, particu- larly for conference room style presentations.)