Which type of data is plotted on a p Chart?

A p Chart, or proportion chart, is specifically designed to monitor the proportion of defective items in a process over time. This type of chart is used for tracking attribute data, which refers to categorical data that can be classified into distinct groups based on qualities or characteristics. For instance, in a manufacturing setting, attribute data may involve classifying products as either "defective" or "non-defective."

The metric utilized in a p Chart is the proportion of defective items, making it essential for assessing processes where the quality is determined by the presence or absence of a characteristic rather than measuring specific values. Attribute data can often be represented as counts or proportions, which aligns perfectly with the focus of a p Chart—monitoring the variation in the proportion of defects across different samples.

In contrast, the other types of data—variables, discrete, and continuous—are not appropriate for a p Chart. Variable data refers to measurements that can take on a range of values (e.g., weight, length), while discrete data involves countable items that do not fit into the binary classification model of attribute data. Continuous data represents measurements that can take on an infinite number of values within a range and is usually plotted on charts designed for continuous data, such as x