The discrete analysis gives an overview about the resulting categories for each tested feature. The displayed numbers indicate the amount a tester mapped a feature (in a row) to one of the categories (in the columns). The rightmost column indicates the winning category based on the majority of votes.
Must-be | Performance | Attractive | Indifferent | Reverse | Questionable | Category | |
---|---|---|---|---|---|---|---|
12 % (6) | 26 % (13) | 38 % (19) | 22 % (11) | 0 % (0) | 2 % (1) | Attractive | |
10 % (5) | 14 % (7) | 40 % (20) | 28 % (14) | 6 % (3) | 2 % (1) | Attractive | |
22 % (11) | 14 % (7) | 8 % (4) | 48 % (24) | 2 % (1) | 6 % (3) | Indifferent* | |
26 % (13) | 16 % (8) | 12 % (6) | 42 % (21) | 0 % (0) | 4 % (2) | Indifferent* | |
12 % (6) | 4 % (2) | 14 % (7) | 58 % (29) | 8 % (4) | 4 % (2) | Indifferent* | |
38 % (19) | 10 % (5) | 6 % (3) | 30 % (15) | 2 % (1) | 14 % (7) | Must-be | |
24 % (12) | 36 % (18) | 18 % (9) | 20 % (10) | 0 % (0) | 2 % (1) | Performance | |
14 % (7) | 14 % (7) | 36 % (18) | 30 % (15) | 0 % (0) | 6 % (3) | Attractive | |
44 % (22) | 8 % (4) | 4 % (2) | 34 % (17) | 0 % (0) | 10 % (5) | Must-be | |
28 % (14) | 2 % (1) | 10 % (5) | 56 % (28) | 2 % (1) | 2 % (1) | Indifferent* |
The continuous analysis pictures the average evaluation of features on a continuous scale. Therefor, the average response for the functional and dysfunctional question is calculated, whereby the response “I dislike it“ gets the value 0 and the response “I like it“ the value 4. Accordingly, the features are put into the 2-dimensional coordinate system.
(Feature is absent) | |||||||||||||||||||||||||||||||||||||
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(Feature is present) |
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The evaluation table gives an overview about which combinations of answers for each tester and feature result in which category. Based on two questions about the presence (functional) and absence (dysfunctional) of the feature, the feature is put in one of the six categories. The table serves you to understand this mapping of answers to category.
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