"A company has a policy of retiring company cars; this policy looks at number of miles driven, purpose of trips, style of car and other features. The distribution of the number of months in service for the fleet of cars is bell-shaped and has a mean of 65 months and a standard deviation of 6 months. Using the empirical rule (as presented in the book), what is the approximate percentage of cars that remain in service between 47 and 59 months

83.85%

Step-by-step explanation:

Given that:

Mean (μ) = 65 months, Standard deviation (σ) = 6 months.

The empirical rule states that about 68% of the data falls within one standard deviation (μ ± σ), 95% of the data falls within two standard deviation (μ ± 2σ) and 99.7% of the data falls within three standard deviation (μ ± 3σ).

For the question above:

68% of the data falls within one standard deviation (μ ± σ) = (65 ± 6) = (59, 71) i.e between 59 months and 71 months

95% of the data falls within one standard deviation (μ ± 2σ) = (65 ± 12) = (53, 77) i.e between 53 months and 77 months

99.7% of the data falls within one standard deviation (μ ± 3σ) = (65 ± 18) = (47, 83) i.e between 47 months and 83 months

The percentage of cars that remain in service between 47 and 59 months = (68% ÷ 2) + (99.7% ÷ 2) = 34% + 49.85 = 83.85%

the equivalent expression are always the hardest ones but you look at the gcf also

step-by-step explanation: