Microsoft Office Tutorials and References
In Depth Information
The appropriateness of the chart type. Just about everyone can
understand a simple column chart, but nontechnical types usually cringe at the
sight of a radar chart.
The overall “style” of the chart, ranging on a scale from informal to
formal. A chart intended for an employee newsletter will probably look
much different than a chart prepared for a Board of Directors meeting.
The choice of colors used in the chart. A chart that looks great in color
may be incomprehensible when printed on a black-and-white printer,
photocopied, or faxed.
The sections that follow expand upon these general points.
When people view a chart, they make the implicit assumption that the chart reflects
the truth. In fact, an attractive chart may even create a sense of accuracy. After all, the
chart-maker surely wouldn’t go through all that work if the numbers weren’t accurate!
But, of course, truth is relative. The accuracy of the data that comprises the chart
is a key consideration. Inaccurate data comes from measurement error and human
error (including incorrect formulas in your worksheet). Only you can determine
whether your data (and calculations that use the data) are accurate.
There are a number of ways in which a chart can present a less-than-truthful
picture. The remainder of this section presents examples that demonstrate various ways
in which charts can mislead the viewer and possibly lead to incorrect conclusions.
Plotting data out of context
Typically, data that’s presented in a chart should be presented in its proper context.
Figure 11-1 shows an example. The top chart displays data for three months and
leaves the impression that there is a downward trend in the numbers. But, when
viewed in the context of the entire year, the last three data points do not seem at all
out of the ordinary.
Plotting percent change versus actual change
Time-based data is often summarized by calculating a percent change from one
period to another. These percentage calculations do not take into account the
magnitude of the values and can therefore mislead the viewer.
The chart in Figure 11-2 displays the percentage change for three products.
Product C, of course, stands out in the chart — even though its total values are
almost insignificant when compared to the other products. The data is completely
accurate, yet the chart is very misleading. Creating a chart from the data in column
D would be a much better choice.