Which of the following data-classification methods selects class break levels by taking the complete range of values and dividing by the desired number of classes?

The method that selects class break levels by taking the complete range of values and dividing by the desired number of classes is known as the Equal Interval classification. This approach involves determining the range of data—subtracting the minimum value from the maximum value—and then dividing that range by the number of classes you wish to create. Each interval is of equal size, providing a straightforward way to categorize data into defined groups.

For example, if the minimum value is 10 and the maximum is 110, and you want to create 5 classes, you would first determine the range (110 - 10 = 100) and then divide by the number of classes (100 / 5 = 20). Thus, each class would represent a range of 20 units, leading to classes defined as 10-30, 30-50, and so on.

Other classification methods have different criteria for establishing their breaks. Quantiles, for instance, distribute data into classes with an equal number of data points, which can lead to varying class intervals based on data distribution. Natural Breaks identifies the points where there are significant gaps in data distribution, and Standard Deviation classifies data based on how far values deviate from the mean. Each of these methods serves