Respuesta :

akiran007

Answer:

The distribution is positively skewed.

Step-by-step explanation:

A measure of skewness is defined in such a way that the measure should always be zero when the distribution is symmetric and measure should be a pure number i.e independent of origin and units of measurement.

The shape of the distribution can be found by finding the coefficient of skewness.

The coefficient of skewness can be found by  

Sk= 3(Mean-Median)/ Standard Deviation

Sk= 3( 50-40)5= 30/5=6

The shape will be positively skewed.

In a positively skewed distribution the mean > median > mode. It has a long right tail.

Using the skewness formula, it is found that the distribution is right-skewed.

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  • The skewness of a data-set with mean M, median [tex]M_e[/tex] and standard deviation s is given by:

[tex]S = \frac{3(M - M_e)}{s}[/tex]

  • If |S| < 0.5, the distribution is said to be symmetric.
  • If S <-0.5, the distribution is left-skewed.
  • If S > 0.5, the distribution is right-skewed.

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  • Mean of 50, thus, [tex]M = 50[/tex]
  • Median of 40, thus [tex]M_e = 40[/tex]
  • Standard deviation of 5, thus, [tex]s = 5[/tex]

The coefficient is:

[tex]S = \frac{3(M - M_e)}{s} = \frac{3(50 - 40)}{5} = \frac{30}{5} = 6[/tex]

Thus, the distribution is right-skewed.

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