you are aw some
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Sadly you are not since you can't even spell the word.
Relative frequency would be better because the two groups may be of different size.
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These help to distribute the frequency much better than the latter. The noise might not be as loud or boisterous this way.
Yes. If the sample is a random drawing from the population, then as the size increases, the relative frequency of each interval from the sample should be a better estimate of the relative frequency in the population. Now, in practical terms, increasing a small sample will have a larger effect than increasing a large sample. For example, increasing a sample from 10 to 100 will have a larger effect than increasing a sample from 1000 to 10,000. The one exception to this, that I can think of, is if the focus of the study is on a very rare occurrence.
There may or may not be a benefit: it depends on the underlying distributions. Using the standard normal distribution, whatever the circumstances is naive and irresponsible. Also, it depends on what parameter you are testing for. For comparing whether or not two distributions are the same, tests such as the Kolmogorov-Smirnov test or the Chi-Square goodness of fit test are often better. For testing the equality of variance, an F-test may be better.
A frequency distribution with the total frequency equated to one hundred and the individual class frequencies expressed in proportion to that figure. :) Im so smart ;) No one better improve this answer.You welcome Person who asked this question.
The different methods evolved separately. Also, different ways are sometimes better in different situations.