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Q: Why relative frequency distribution better than frequency distribution?

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The 2k or 2 to K rule is used to determine the number of classes for a frequency distribution. The 2k rule should be used as a guide more than a dictator of determining the number of classes for a frequency distribution.

The shape of a t distribution changes with degrees of freedom (df). As the the df gets very large the shape of the t distribution will begin to look similar to that of a normal distribution. However, the t distribution has more variability than a normal distribution; especially when the df are small. When this is the case the t distribution will be flatter and more spread out than the normal distributions.

As the mean is greater than the median it will be positively skewed (skewed to the right), and if the median is larger than the mean it will be negatively skewed (skewed to the left)

Scores on the SAT form a normal distribution with a mean of µ = 500 with σ = 100. What is the probability that a randomly selected college applicant will have a score greater than 640?

Suppose you could call it the Gaussian Distribution or the Laplace-Gauss (not to be confused with the Laplace distribution which takes an absolute difference from the mean rather than a squared error)... however the Brits had no one to name this distribution after (not the German and French names) and because it is the ubiquitous distribution they just called it... well the NORMAL!!

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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.

you are aw some * * * * * 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.

It is not. It depends on what question you want to answer. They are both equally informative, but in different circumstances.the CRFD can be used to determine a summary of proportion of observations that lies above(or below) a particular value in a data set which the RFD cannot

The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.

The wave length and frequency of course vary, the frequency ranges from 3kHz to 300 GHz. The wavelengths are longer than infrared.

If the cumulative relative frequency when the variable X takes the value x, it means that 0.4 (or 40%) of the values of the variable X are less than or equal to x.

The 2k or 2 to K rule is used to determine the number of classes for a frequency distribution. The 2k rule should be used as a guide more than a dictator of determining the number of classes for a frequency distribution.

Violet light has a higher frequency than red light by roughly a factor of 2.

It may not be better, but there is a lot of information on the normal distribution. It is one of the most widely used in statistics.

complexity is low than spatial

In a bar graph, the height of the bars is relative to the frequency. In a histogram, the area of the bars is relative to the frequency. Because it deals with area, the label on the y-axis is "frequency density" rather than just "frequency"

It's not a problem. But it's better when FSB frequency is higher than RAM frequency.

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