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The third moment. That is, the expected value of the cubes of the deviations from the mean.

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10y ago

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What are the formulas in probability?

There are many, many formulae:for different probability distribution functions,for cumulative distribution functions,for moment generating functions,for means, variances, skewness, kurtosis and higher moments.There are many, many formulae:for different probability distribution functions,for cumulative distribution functions,for moment generating functions,for means, variances, skewness, kurtosis and higher moments.There are many, many formulae:for different probability distribution functions,for cumulative distribution functions,for moment generating functions,for means, variances, skewness, kurtosis and higher moments.There are many, many formulae:for different probability distribution functions,for cumulative distribution functions,for moment generating functions,for means, variances, skewness, kurtosis and higher moments.


Is it true some normal probability distributions are positively skewed?

No. The Normal distribution is symmetric: skewness = 0.


If coefficient of skewness equals 0 then what would you say about the skewness of the distribution?

if coefficient of skewness is zero then distribution is symmetric or zero skewed.


What is skewness how would you find it in a non symmetrical distribution?

Skewness is a measure of the extent to which the probability distribution of a random variable lies more to one side of the mean, as opposed to it being exactly symmetrical.If μ and s are the mean and standard deviation of a random variable X, thenSkew(X) = Expected value of [(X - μ)/s]3


The use of Pearson Coefficient of Skewness?

Ah, the Pearson Coefficient of Skewness, fancy term for measuring the asymmetry of a probability distribution. It tells you if your data is skewed to the left, right, or if it's all hunky-dory symmetrical. Just plug in your numbers, crunch some math, and voila, you'll know how wonky your data is. Just remember, skewness doesn't lie, so embrace those skewed curves!


Is not a characteristics of a normal distribution.?

Skewness is not a characteristic.


What shows distribution of data on a number line?

A probability density function.


How do the highest and lowest possible values for the variable compare in their probability of occurring to the values in the middle of the distribution?

The answer will depend on the skewness of the distribution.The Poisson distribution is defined for non-negative integers: 0, 1, 2, 3, 4 etc. So the lowest value is 0.For a Poisson distribution with parameter l=1 (when it is very skew), the probability of the lowest two values, 0 and 1, is 0.368 each and the probability tails off rapidly for higher values.The answer will depend on the skewness of the distribution.The Poisson distribution is defined for non-negative integers: 0, 1, 2, 3, 4 etc. So the lowest value is 0.For a Poisson distribution with parameter l=1 (when it is very skew), the probability of the lowest two values, 0 and 1, is 0.368 each and the probability tails off rapidly for higher values.The answer will depend on the skewness of the distribution.The Poisson distribution is defined for non-negative integers: 0, 1, 2, 3, 4 etc. So the lowest value is 0.For a Poisson distribution with parameter l=1 (when it is very skew), the probability of the lowest two values, 0 and 1, is 0.368 each and the probability tails off rapidly for higher values.The answer will depend on the skewness of the distribution.The Poisson distribution is defined for non-negative integers: 0, 1, 2, 3, 4 etc. So the lowest value is 0.For a Poisson distribution with parameter l=1 (when it is very skew), the probability of the lowest two values, 0 and 1, is 0.368 each and the probability tails off rapidly for higher values.


The Pearson's coefficient of skewness is a measure of distribution's symmetry?

It is a descriptive statistical measure used to measure the shape of the curve drawn from the frequency distribution or to measure the direction of variation. It is a measure of how far positively skewed (below the mean) or negatively skewed (above the mean) the majority (that's where the mode comes in) of the data lies. Useful when conducting a study using histograms. (mean - mode) / standard deviation. or [3(Mean-Median)]/Standard deviation


In which situations mean and median are not same?

If there is any skewness in the distribution.


What is the values of the skewdness and kurtosis coefficient for the normal distribution 0 and 3 respectively?

No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.


What are the Similarities of discrete probability distribution and continuous probability distribution?

They are probability distributions!