Скачать или смотреть How to use the 2k Rule | How to Determine the Perfect Class Size for Your Frequency Distribution|

This is when you having confused what is the proportional class size to your data size, and how to determine your class size with the 2k rule.

The 2k rule is a heuristic used in statistics to determine the appropriate class size for frequency distributions. The rule suggests that the number of classes in a frequency distribution should be approximately equal to the square root of the number of observations in the data set. In other words, if you have 100 observations, the recommended number of classes would be 10 (since 10 x 10 = 100).

The purpose of the 2k rule is to create an appropriate balance between the level of detail in the data and the clarity of the presentation. If there are to few classes, important features of the data may be lost. If there are too many classes, the distribution may become too complex and difficult to interpret.

The rule is not an exact method, and some discretion is required in its application. Other factors, such as the range and distribution of the data, should also be taken into account. However, the 2k rule provides a useful starting point for determining the appropriate class size in a frequency distribution.

#maths
#mathematics
#statistics