E ( X ) = ( 6 + 8 + K + 2 + 4 + K + 10 + 3 K ) / 8 = ( 30 + 5 K ) / 8 E(X)=( 6+8+K+2+4+K+10+3K)/8=(30+5K)/8 E ( X ) = ( 6 + 8 + K + 2 + 4 + K + 10 + 3 K ) /8 = ( 30 + 5 K ) /8
K = ( 8 E ( X ) − 30 ) / 5 = ( 8 ⋅ 9.375 − 30 ) / 5 = 9 K=(8E(X)-30)/5=(8\cdot 9.375-30)/5=9 K = ( 8 E ( X ) − 30 ) /5 = ( 8 ⋅ 9.375 − 30 ) /5 = 9
E ( X 2 ) = ( 6 2 + 8 2 + 9 2 + 2 2 + 4 2 + 9 2 + 1 0 2 + 2 7 2 ) / 8 = 138.875 E(X^2)=(6^2+8^2+9^2+2^2+4^2+9^2+10^2+27^2)/8=138.875 E ( X 2 ) = ( 6 2 + 8 2 + 9 2 + 2 2 + 4 2 + 9 2 + 1 0 2 + 2 7 2 ) /8 = 138.875
V a r ( X ) = E ( X 2 ) − E ( X ) 2 = 138.875 − 9.37 5 2 = 50.98 Var(X)=E(X^2)-E(X)^2=138.875-9.375^2=50.98 Va r ( X ) = E ( X 2 ) − E ( X ) 2 = 138.875 − 9.37 5 2 = 50.98
σ ( X ) = V a r ( X ) = 50.98 = 7.14 \sigma(X)=\sqrt{Var(X)}=\sqrt{50.98}=7.14 σ ( X ) = Va r ( X ) = 50.98 = 7.14
Now we calculate Z-scores of each value of the random variable X:
X ~ = ( X − E ( X ) ) / σ ( X ) \tilde X=(X-E(X))/\sigma(X) X ~ = ( X − E ( X )) / σ ( X )
( 6 − 9.375 ) / 7.14 = − 0.4727 (6-9.375)/7.14=-0.4727 ( 6 − 9.375 ) /7.14 = − 0.4727
( 8 − 9.375 ) / 7.14 = − 0.1926 (8-9.375)/7.14=-0.1926 ( 8 − 9.375 ) /7.14 = − 0.1926
( 9 − 9.375 ) / 7.14 = − 0.0525 (9-9.375)/7.14=-0.0525 ( 9 − 9.375 ) /7.14 = − 0.0525
( 2 − 9.375 ) / 7.14 = − 1.0329 (2-9.375)/7.14=-1.0329 ( 2 − 9.375 ) /7.14 = − 1.0329
( 4 − 9.375 ) / 7.14 = − 0.7528 (4-9.375)/7.14=-0.7528 ( 4 − 9.375 ) /7.14 = − 0.7528
( 9 − 9.375 ) / 7.14 = − 0.0525 (9-9.375)/7.14=-0.0525 ( 9 − 9.375 ) /7.14 = − 0.0525
( 10 − 9.375 ) / 7.14 = 0.0875 (10-9.375)/7.14=0.0875 ( 10 − 9.375 ) /7.14 = 0.0875
( 27 − 9.375 ) / 7.14 = 2.4684 (27-9.375)/7.14=2.4684 ( 27 − 9.375 ) /7.14 = 2.4684
The coefficient of skewness is by definition
E ( X ~ 3 ) = ( − 0.472 7 3 − 0.192 6 3 − 0.052 5 3 − 1.032 9 3 − 0.752 8 3 − 0.052 5 3 + 0.087 5 3 + 2.468 4 3 ) / 8 = 13.4 E(\tilde X^3)=(-0.4727^3-0.1926^3-0.0525^3-1.0329^3-0.7528^3-0.0525^3+0.0875^3+2.4684^3)/8=13.4 E ( X ~ 3 ) = ( − 0.472 7 3 − 0.192 6 3 − 0.052 5 3 − 1.032 9 3 − 0.752 8 3 − 0.052 5 3 + 0.087 5 3 + 2.468 4 3 ) /8 = 13.4
One can see that E ( X ~ 3 ) > > 0 E(\tilde X^3)>>0 E ( X ~ 3 ) >> 0 , this means that some values of X (X=27) are located far to the right of the average value. The value X = 27 X=27 X = 27 one should consider as extremal (unusual) big.
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