A Quantitative Multi-Response Set refers to a data structure where multiple quantitative (numeric) responses are associated with a single conceptual question or observation.
To create a quantitative MR set, a dataset must include multiple records of measurements, quantities, counts, or other numerical values related to a single context. Once the quantitative MR-set is assembled in Datatail, you can instantly visualize the weighted mean for each parameter.
For example: "Please rate your satisfaction with your store visit on a scale from 1 to 10?"
Respondent | Store1 | Store2 | Store3 |
1 | 6 | 5 | 5 |
2 | 7 | 6 | 3 |
3 | 5 | 3 | 3 |
4 | 8 | 3 | 4 |
5 | 7 | 6 | 4 |
6 | 7 | 5 | 4 |
7 | 5 | 7 | 6 |
8 | 6 | 4 | 7 |
9 | 7 | 3 | 4 |
10 | 4 | 6 | 3 |
After loading the dataset we get 3 numeric variables to assemble the MR-set.
To create the quantitative MR-set
select all numerical variables with certain parameters;
click in the ‘Declare MR-set’ icon
;choose the ‘Quantitative’ type of MR-set;
tick the checkbox ‘Automatically add matching variables to this MR-set’, if you want new variables with the same code pattern to be automatically added to the set in future waves, without the need to rebuild it.
The practical value of calculations with this MR-set lies in obtaining the average estimates for each store. For accurate crosstab calculations, ensure the MEAN metric is applied, as Vert% is not meaningful for this type of MR-set.
