Complete the following steps if your attribute data are in a single column of the worksheet.
C1-T | C2 | C3 | C4 |
---|---|---|---|
Appraiser | Sample | Rating | Standard |
Simpson | 1 | 2 | 2 |
Montgomery | 1 | 2 | 2 |
Holmes | 1 | 2 | 2 |
Duncan | 1 | 1 | 2 |
Hayes | 1 | 2 | 2 |
Complete the following steps if your ratings from each appraiser are in separate columns of the worksheet.
The order of the appraiser names must match the order in the worksheet.
C1 | C2 | C3 | C4 | C5 | C6 | C7 |
---|---|---|---|---|---|---|
Part | Standard | Simpson | Montgomery | Holmes | Duncan | Hayes |
1 | 2 | 2 | 2 | 2 | 1 | 2 |
2 | -1 | -1 | -1 | -1 | -2 | -1 |
3 | 0 | 1 | 0 | 0 | 0 | 0 |
4 | -2 | -2 | -2 | -2 | -2 | -2 |
5 | 0 | 0 | 0 | 0 | -1 | 0 |
Enter the column that contains the known reference rating for each sample. The column can contain either numeric or text attributes, but the data type must match the response type.
If you have a known reference value for each sample, you can assess the correctness of each appraiser's ratings across trials. If you select Categories of the attribute data are ordered, Minitab also provides Kendall's correlation coefficients.
Select to specify that the data have more than two levels and are ordinal. If your data are ordinal, Minitab provides both kappa statistics and Kendall's coefficients of concordance to evaluate the association between appraiser ratings.