In statistics, the context of the data is critical to decide the right statistical method. For instance, taking the average of all the numbers to get a common phone number for the class is meaningless. For the purpose of analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio. The data that cannot be measured or ordered but can be grouped into categories fall under the nominal level of measurement. For example, one cannot measure or place hairstyles in a particular order but can group them into different categories. Although these groups can be numbered for the sake of convenience, the difference between these numbers or the average of these numbers is meaningless. Survey responses such as like-dislike, yes-no, or political party affiliations also fall under the nominal level of measurement.