In both clinical research and quality improvement, it is commonplace to compare groups of patients (eg, treatment versus control, pre versus post, hospital A versus hospital B) on a variety of characteristics. These characteristics usually take the form of (1) continuous data with comparisons made with t tests (for normal distributions) or Wilcoxon rank-sum tests (for nonnormal distributions) or (2) categorical data. Continuous data are data that can take almost any numeric value within a given range and can be subdivided into smaller and smaller increments without losing the meaning associated with the data. Examples of continuous data commonly found in health care include age, height, weight, temperature, or cost. Categorical data, as the name suggests, can be put into nonoverlapping categories, groups, or classes. Some examples of categorical data that frequently occur in health care are gender, disposition, and skill level (eg, RN, LPN, AHT). Antibiotic receipt, chest radiograph...

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