Quick fact: linear graphs do a number of things to data that can have negative effects on interpretative behavior. For example, linear graphs always show changes between different magnitudes in a manner that can mislead the chart viewer. Take the data set below:
Table 1: Data showing two sets of data at different magnitudes.
What does that data look like on a linear graph? Behold:
Figure 1. A linear graph showing the change between two sets of data with different magnitudes.The two data paths show that both appear to have a flat trend. The upper series, which has a higher magnitude than the lower series, looks almost the same in terms of growth -- that is, very little.
But when we plug the data into Chartlytics, well as Emeril Lagasse would say, “Bam!”
Figure 2. Chartlytics using a Standard Celeration Chart to show the change between two sets of data with different magnitudes.
The Standard Celeration Chart differs from a linear graph in that it shows ratio change rather than absolute amounts of change. The result of such an important characteristic is that ratio change better represents differences between data at divergent magnitudes.
In the data charted, a change from 3 to 5 (66.67% increase) is much more significant than a change from 123 to 129 (4.88% increase). Chartlytics Standard Celeration Chart (SCC) clearly shows the difference in percent increase. A linear graph may not, hiding the clinical significance of change.
A change from 1 to 2 forms a x2 change, a 100% increase. Going from 10 to 20 also has the same ratio, a x2 change or a 100% increase. Therefore, when placing data on the SCC it will evenhandedly show changes between different magnitudes. Linear charts do not.
This ends your quick fact!