Data Moves

● Ordering: (An example: Ordering cases along one numeric attribute going from lowest to highest value or vice versa);
● Grouping:  (An example: Separating cases into two groups based on a dichotomous attribute, such as “went to the Emergency Department” or “did not go to the Emergency Department”);
● Filtering:  (An example: Filtering out all values that an attribute can take except one in order to focus only on that one attribute, such as filtering out injuries to all body parts except the head so as to focus specifically on head injuries);
● Summarizing:  (An example: Computing a statistic across individual cases, such as looking at the rate of injuries for a sport by taking the total number of injuries for the and dividing it by the number participants in that sport);
● Making a visual representation:  (An example: Creating a graph that shows how cases are distributed across one or more attributes, such as graphing injury episodes as a function of “age group” and “activity at time of the injury,” with one attribute on one axis of the graph and the other on the other axis).