Читать книгу Medical Statistics - David Machin - Страница 35

Binary data are the simplest type of data in which each individual has a label that takes one of two values such as: male or female; corn healed or not healed. A simple summary would be to count the different types of label. However, a raw count is rarely useful. For example, in Table 2.1 there are more non‐smokers in the scalpel group (40 out of 99 or 40%) compared to corn plaster group (34 out of 98 or 35%). It is only when this number is expressed as a proportion that it becomes useful. Hence the first step to analysing categorical data is to count the number of observations in each category and express them as proportions of the total sample size.