Suppose that shoe sizes of American women have a bell-shaped distribution with a mean of 8.06 and a standard deviation of 1.52. Using the empirical rule, what percentage of American women have shoe sizes that are greater than 11.1? Please do not round your answer.
In statistics, the 68–95–99.7 rule, also known as the
three-sigma rule or empirical rule, states that nearly all values
lie within three standard deviations of the mean in a normal
distribution.
About 68.27% of the values lie within one standard deviation of the
mean.
Similarly, about 95.45% of the values lie within two standard deviations of the mean.
Nearly all (99.73%) of the values lie within three standard
deviations of the mean.
where x is an observation from a normally distributed random
variable, μ is the mean of the distribution, and σ is its standard
deviation:
P( μ – σ ≤ x ≤ μ + σ ) ≈ 0.6827
P( μ –2σ ≤ x ≤ μ + 2σ ) ≈ 0.9545
P( μ –3σ ≤ x ≤ μ + 3σ ) ≈ 0.9973
Here μ = 8.06 and σ = 1.52
μ + σ = 9.58 ; μ – σ = 6.54
μ + 2σ = 11.1 ; μ – 2σ = 5.02
So, Using the empirical rule, the approximate percentage of
American women have shoe sizes that are no more then 11.1 and no
less than 5.02 = 95.45%
So, Using the empirical rule, the approximate percentage of
American women have shoe sizes that are no more then 11.1 = 95.45%
+ (100-95.45)/2 % = 97.725%
So, Using the empirical rule, the approximate percentage of American women have shoe sizes that are greater than 11.1
= 100%-97.725% =2.28%
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