10. (a) For a distribution, the mean is 10, variance is 16, the skewness 4
sk is +1 and kurtosisÂ
b2
 is 4. Obtain the first four moments about the origin i.e. zero. Comment upon theÂ
nature of the distribution.
Mean "= m_1\u2032 =10" , variance ="m_2 =16" , coefficient of skewness "= \\gamma_1 = +1" , coefficient of kurtosis is "\\beta_2 = 4."
First moment about the origin is
Mean "= m_1\u2032 = 10" .
Next, Variance "= \ud835\udc5a_2 = 16 =\\dfrac{\u2211 x}{n}-(\\dfrac{\\sum x}{n})^2"
Second moment about the origin is "m_2=\\dfrac{\\sum x^2}{n}=m_2+\\mu_1^2=Variance+(\\dfrac{\\sum x}{n})^2=16+10^2=116"
Coefficient of skewness is +1:
"\\gamma1 = +1 =\\dfrac{\ud835\udc5a_3}{\ud835\udc5a_2^{\\frac{3}{2}}}\\rightarrow \ud835\udc5a_3 = \ud835\udc5a_2^{\\frac{3}{2}} = 16^{\\frac{3}{2}} = 64"
   Â
Coefficient of kurtosis is 4:
"\\beta_2 = 4\\\\\n\n\\dfrac{\ud835\udc5a_4}{\ud835\udc5a_2^2} = 4 \\rightarrow \ud835\udc5a_4 = 4(16)^2 = 1024"
Third moment about the origin is
"\ud835\udc5a_3\u2032 = \ud835\udc5a_3 + 3\ud835\udc5a_2\ud835\udc5a_1\u2032 + \ud835\udc5a_1\u2032 ^3 = 64 + 3(16)(10) + 10^3 = \ud835\udfcf\ud835\udfd3\ud835\udfd2\ud835\udfd2"
Fourth moment about the origin is
"\ud835\udc5a_4\u2032 = \ud835\udc5a_4 + 4\ud835\udc5a_3\ud835\udc5a_1\u2032 + 6\ud835\udc5a_2\ud835\udc5a_2\u2032 + \ud835\udc5a_1\u2032 ^4 = 1024 + 4(64)(10) + 6(16)102 + 10^4 = \ud835\udfd0\ud835\udfd1\ud835\udfcf\ud835\udfd6\ud835\udfd2"
It is a positively skewed distribution.
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