The SUMI data is analysed by a program called SUMISCO. The raw question data is coded, combined, and transformed into a Global subscale, and five addiitional subscales called Efficiency, Affect, Helpfulness, Controllability, and Learnability. The z-score transformation is used to make the scales have an expected (population) mean of 50, and a standard deviation of 10.
The basic output is in a .csv type of file which can be opened by many spreadsheet programs. Graphs and data cross-tabulations can be done, but at present this costs extra.
Here is an example of a table of scored SUMI data. Next to each entry the responses to the additional questions are given (the last two additional questions from the standard site are not shown in this page.)
| Global | Eff | Aff | Helpf | Contr | Learna | What, in general, do you use this software for? | How important for you is the kind of software you have just been rating? | How would you rate your software skills and knowledge? |
|---|---|---|---|---|---|---|---|---|
| 47 | 38 | 45 | 50 | 42 | 47 | Looking at my account | 1 | 2 |
| 40 | 32 | 51 | 41 | 38 | 32 | Just browsing products | 1 | 3 |
| 64 | 63 | 59 | 57 | 48 | 52 | Account | 2 | 2 |
| 51 | 27 | 56 | 54 | 47 | 25 | paying bills | 2 | 2 |
| 39 | 28 | 42 | 40 | 28 | 53 | 1 | 2 | |
| 48 | 39 | 50 | 44 | 38 | 54 | checking my account | 2 | 2 |
| 38 | 29 | 32 | 52 | 36 | 30 | ? | 1 | 3 |
| 41 | 34 | 66 | 50 | 39 | 24 | payment | 2 | 3 |
| 56 | 60 | 53 | 57 | 49 | 43 | bills | 2 | 2 |
| 58 | 60 | 58 | 59 | 41 | 59 | keeping up to date | 3 | 2 |
| 47 | 50 | 36 | 44 | 41 | 43 | checking | 2 | 2 |
| 45 | 47 | 33 | 37 | 52 | 56 | account | 1 | 2 |
| 40 | 28 | 42 | 54 | 43 | 24 | looking at adverts | 3 | 3 |
| 31 | 32 | 29 | 40 | 25 | 34 | bills | 1 | 3 |
| 31 | 38 | 39 | 25 | 34 | 56 | accounts | 1 | 2 |
| 53 | 49 | 63 | 59 | 58 | 28 | [deleted] | 1 | 3 |
| 55 | 62 | 48 | 51 | 43 | 43 | bills | 1 | 3 |
| 67 | 71 | 69 | 59 | 61 | 67 | keeping in touch with the company | 2 | 1 |
| 32 | 35 | 26 | 40 | 25 | 32 | my usage | 1 | 2 |
Various summary statistics are computed at the bottom of the data table.
| Global | Eff | Aff | Helpf | Contr | Learna | |
|---|---|---|---|---|---|---|
| 19 | 19 | 19 | 19 | 19 | 19 | (n) |
| 46.47 | 43.26 | 47.21 | 48.05 | 41.47 | 42.21 | (Mean) |
| 10.27 | 13.69 | 12.38 | 8.99 | 9.52 | 13.02 | (Standard Dev) |
| 66.60 | 70.09 | 71.48 | 65.66 | 60.13 | 67.73 | (Upper Fence) |
| 26.35 | 16.44 | 22.94 | 30.44 | 22.82 | 16.69 | (Lower Fence) |
| 2.37 | 3.15 | 2.85 | 2.07 | 2.20 | 3.00 | (Standard Error of Mean) |
| 51.11 | 49.43 | 52.80 | 52.12 | 45.78 | 48.08 | (Upper 95% CL) |
| 46.47 | 43.26 | 47.21 | 48.05 | 41.47 | 42.21 | (Mean) |
| 41.83 | 37.09 | 41.62 | 43.99 | 37.17 | 36.34 | (Lower 95% CL) |
The Item Consensual Analysis shows the difference between the observed frequenceis of response to each question and the frequencies of response expected on the basis of the standardisation base. The summary statistic is chi square which should be read with df = 2. However, you should not place too much emphasis on the absolute value of the statistic, simply to observe which items have the biggest differences between the observed and the expected, and in which category of response the biggest differences are found. Items are printed out in order of the total chi square value
Only the first three items from this analysis are shown on this page.
| Item 50 | I have to look for assistance most times when I use this software. | |||
| Agree | Undecided | Disagree | ||
| Obs | 9 | 6 | 4 | |
| Exp | 2.25 | 2.62 | 14.12 | |
| Chi | 20.18 | 4.34 | 7.25 | 31.77 |
| Item 18 | There is never enough information on the screen when it's needed. | |||
| Agree | Undecided | Disagree | ||
| Obs | 12.00 | 4.00 | 3.00 | |
| Exp | 3.18 | 4.12 | 11.70 | |
| Chi | 24.48 | 0.00 | 6.47 | 30.95 |
| Item 16 | This software seems to disrupt the way I normally like to arrange my work. | |||
| Agree | Undecided | Disagree | ||
| Obs | 7.00 | 9.00 | 3.00 | |
| Exp | 1.68 | 4.27 | 13.05 | |
| Chi | 16.82 | 5.24 | 7.74 | 29.80 |
The following tables are not provided with the standard SUMI output, but they show how the spreadsheet can be analysed to releal different patterns and trends in the data.
Here is an example of how the basic data can be cross-tabulated. In the following example, the SUMI profiles are tabulated against the responses to the question How important for you is the kind of software you have just been rating? For each of the response categories, means have been computed.
| Global | Eff | Aff | Helpf | Contr | Learna | How important for you is the kind of software you have just been rating? |
|---|---|---|---|---|---|---|
| 47 | 38 | 45 | 50 | 42 | 47 | 1 |
| 40 | 32 | 51 | 41 | 38 | 32 | 1 |
| 39 | 28 | 42 | 40 | 28 | 53 | 1 |
| 38 | 29 | 32 | 52 | 36 | 30 | 1 |
| 45 | 47 | 33 | 37 | 52 | 56 | 1 |
| 31 | 32 | 29 | 40 | 25 | 34 | 1 |
| 31 | 38 | 39 | 25 | 34 | 56 | 1 |
| 53 | 49 | 63 | 59 | 58 | 28 | 1 |
| 55 | 62 | 48 | 51 | 43 | 43 | 1 |
| 42.11 | 39.44 | 42.44 | 43.89 | 39.56 | 42.11 | (average) |
| 32 | 35 | 26 | 40 | 25 | 32 | 1 |
| 64 | 63 | 59 | 57 | 48 | 52 | 2 |
| 51 | 27 | 56 | 54 | 47 | 25 | 2 |
| 48 | 39 | 50 | 44 | 38 | 54 | 2 |
| 41 | 34 | 66 | 50 | 39 | 24 | 2 |
| 56 | 60 | 53 | 57 | 49 | 43 | 2 |
| 47 | 50 | 36 | 44 | 41 | 43 | 2 |
| 67 | 71 | 69 | 59 | 61 | 67 | 2 |
| 50.75 | 47.38 | 51.88 | 50.63 | 43.50 | 42.50 | (average) |
| 58 | 60 | 58 | 59 | 41 | 59 | 3 |
| 40 | 28 | 42 | 54 | 43 | 24 | 3 |
| 49.00 | 44.00 | 50.00 | 56.50 | 42.00 | 41.50 | (average) |
Here, the responses to the question What, in general, do you use this software for? have been tabulated in decreasing order of the Global score for each respondent.
| Global | What, in general, do you use this software for? |
|---|---|
| 67 | keeping in touch with the company |
| 64 | Account |
| 58 | keeping up to date |
| 56 | bills |
| 55 | bills |
| 53 | [deleted] |
| 51 | paying bills |
| 48 | checking my account |
| 47 | Looking at my account |
| 47 | checking |
| 45 | account |
| 41 | payment |
| 40 | Just browsing products |
| 40 | looking at adverts |
| 39 | |
| 38 | ? |
| 32 | my usage |
| 31 | bills |
| 31 | accounts |