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Answer :
Final answer:
In establishing classes for a frequency distribution, more isn't always better. Ideally, there should be between 5 and 20 classes, depending on the data. The goal is to use a number of classes that best represents the data distribution.
Explanation:
When establishing classes for a frequency distribution, it is not necessarily true that more classes will lead to a better frequency distribution. The number of classes you use will depend on the data you are analysing. Frequency distribution is a statistical tool that presents data in a manner that it provides the number (frequency) of occurrences of different data values in a dataset.
When establishing classes, the ideal number is often somewhere between 5 and 20. More than that can overcomplicate your analysis by being too detailed and fragmenting your data excessively, and less than that can oversimplify your representation by missing out on subtle trends and variations. Thus balance is requisite, too few and you might miss important information, too many and your data might become difficult to interpret.
The goal is to choose a number of classes that best represents the spread and shape of the distribution. One common rule of thumb is the 'square root rule', which suggests using the square root of the number of data points in your set as the number of classes. But again, this is more of a starting point and should not be considered a hard and fast rule.
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