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possible subjective rating on the scale was 4. So we just divide the score obtained
for each participant by the corresponding maximum to get the percentage.
In the case of time data, it's a little trickier, as there's not a predefined “best” or
“worst” time—the ends of the scale are not known beforehand. One way of han-
dling this would be to have several experts do the task and treat the average of their
times as the “best” time. Another way is to treat the fastest time obtained from the
participants in the study as the “best” (25 seconds, in this example), the slowest
time as the “worst” (70 seconds, in this example), and then express other times in
relation to those. Specifically, you divide the difference between the longest time
and the observed time by the difference between longest and shortest times. This
way, the shortest time becomes 100% and the longest becomes 0%. Using that
method of transforming the data, you get the percentages shown in Table 8.3 .
Table 8.3 Data from Table 8.2 transformed to percentages a .
Participant # Time Tasks Rating Average
1 11% 47% 60% 39%
2 44% 60% 65% 56%
3 80% 87% 78% 81%
4 0% 40% 43% 28%
5 93% 73% 80% 82%
6 40% 60% 83% 61%
7 27% 53% 63% 48%
8 22% 47% 35% 35%
9 100% 60% 95% 85%
10 33% 67% 90% 63%
a For task completion data, the score was divided by 15. For rating data, the score was divided by 4. For time
data, the difference between the longest time (70) and the observed time was divided by the difference between
longest (70) and shortest (25) times.
Table 8.3 Data from Table 8.2 transformed to percentages a .
a For task completion data, the score was divided by 15. For rating data, the score was divided by 4. For time
data, the difference between the longest time (70) and the observed time was divided by the difference between
longest (70) and shortest (25) times.
We're grateful to David Juhlin, of the Bentley University Design and Usability Center,
for suggesting this transformation of time data. In the first edition of this topic we used
a different method, which resulted in a nonlinear transformation. This new approach is
linear and more appropriate.
TRANSFORMING TIME DATA IN EXCEL
Here are the steps for transforming time data to percentages using these rules in Excel:
1. Enter the raw times into a single column in Excel. For this example, we will assume
they are in column “A” and that you started on row “1”. Make sure there are no
other values in this column, such as an average at the bottom.
 
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