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Use the Kolmogorov Smirnoff goodness-of-fit test.

A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical.

A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such.

The pearson's skew equation is

skew p= (3 (mean - median)) / (SD(x) SD(y))

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Q: How do one determine when a data is normally distributed?
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Differeciate between mode mean and median?

All three are measures of distribution. they hep us understand the distribution of a series of data points. or otherwise said, if you had to guess what something was and you had a whole bunch of estimates, what is the best guess. If the data has a couple spikes (a modal distribution) say there were a few ones, a couple twos, a whole bunch of threes, a few fours, a whole bunch of fives, and a few sixes, than the graph would spike at three and five. To generate a best guess from a set of data that is "modal" you use the "mode". If the data is non-modal but leans toward one end or the other. Say a lot of ones, a lot of twos, good number of threes, some fours, some fives, we'd say this data is "skewed". The best guess for a skewed distribution of data is going to be the median which is the mathematical middle point in a rank order list of data points. If the data was "normally distributed" or had a few ones, few more twos, bunch of threes, few less fours, and only a few fives than we'd say the data was normally distributed, or a "bell curve". In the case of normally distributed data the mean is your best measure. all three are averages. all three describe a collection of data. Which of the three best describes the data depends on the data distribution.


Why is it that only one normal distribution table is needed to find any probability under the normal curve?

Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean. That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5). Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.


The annual precipitation for one city is normally distributed with mean of 38.9 inches and a standard deviation of 3.3 inches Find the 20th percentile?

45.665 inches Type your answer here... what is the answer??


What does one use a bandwidth calculator for?

One would use a bandwidth calculator to see how much data that they are using. Normally it goes by month long periods and you could measure it by that standard.


What is the average of 48 and 67?

Normally, at least two numbers are used to determine an average. If there is only one number, then the average is the number itself, so the answer is 48.