Almost all types of data can be analyzed for statistical significance, whether political, scientific, medical, economic, or financial. The most common forms of data analyzed in significance testing are binary data, such as simple yes-no responses to polls, and discrete or count data, such as the number of clicks on an online advertisement. A third form, known as continuous data, is about a range of values rather than specific binary or count values. For example, a study of consumer spending at supermarkets might track it against the length of time shoppers are in the stores.