Given the first 4 central moments of a random variable x are 0,0.566,0.393 and 0.756 respectively, find the moment coefficient of skewness and kurtosis and interpret them.
Solution:
First central moment"=E(X)=\\mu=0"
Second central moment"=E[(X-\\mu)^2]=E[(X-0)^2]=E[(X)^2]=0.566"
Third central moment"=E[(X-\\mu)^3]=E[(X-0)^3]=E[(X)^3]=0.393"
Fourth central moment"=E[(X-\\mu)^4]=E[(X-0)^4]=E[(X)^4]=0.756"
Now, "Var[X]=\\sigma^2=" Second central moment"=0.566"
So, "\\sigma=\\sqrt{0.566}=0.752329"
Next, "Skewness(X)=\\dfrac{E[(X-\\mu)^3]}{\\sigma^3}=\\dfrac{0.393}{0.752329^3}=0.92293"
And, "Kurtosis(X)=\\dfrac{E[(X-\\mu)^4]}{\\sigma^4}=\\dfrac{0.756}{0.752329^4}=2.35988"
We know that for skewness is that if the number is greater than +1 or lower than –1, this is an indication of a substantially skewed distribution. Here, we get Skewness=0.92293 <+1, this shows there is no skewed distribution.
For kurtosis, we know that if the number is greater than +1, the distribution is too peaked.
Here, Kurtosis=2.35988>+1, this shows the distribution is too peaked.
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