Answer:
1) Between 12.5 miles and 21.7 miles.
2) b) 75%
3) c) 95%
4) Between 13.7 miles and 20.5 miles.
Step-by-step explanation:
Empirical Rule:
The Empirical Rule states that, for a normally distributed random variable:
68% of the measures are within 1 standard deviation of the mean.
95% of the measures are within 2 standard deviations of the mean.
99.7% of the measures are within 3 standard deviations of the mean.
Chebyshev Theorem:
The Chebyshev Theorem can also be applied to non-normal distribution. It states that:
At least 75% of the measures are within 2 standard deviations of the mean.
At least 89% of the measures are within 3 standard deviations of the mean.
An in general terms, the percentage of measures within k standard deviations of the mean is given by .
1) According to Chebyshev's theorem, at least 36% of the commute distances lie between miles and miles.
Within k standard deviations of the mean, and k is found when . So
Within 1.25 standard deviations of the mean.
1.25*3.7 = 4.6 miles
17.1 - 4.6 = 12.5 miles
17.1 + 4.6 = 21.7 miles
Between 12.5 miles and 21.7 miles.
2) According to Chebyshev's theorem, at least of the commute distances lie between 9.7 miles and 24.5 miles.
17.1 - 9.7 = 24.5 - 17.1 = 7.4 miles, so within 2 standard deviations of the mean, which is 75%, option B.
3) Suppose that the distribution is bell-shaped. According to the empirical rule, approximately of the commute distances lie between 9.7 miles and 24.5 miles.
Within 2 standard deviations of the mean, by the Empirical Rule, which is 95%, option c.
4) Suppose that the distribution is bell-shaped. According to the empirical rule, approximately 68% of the commute distances lie between miles and miles.
Within 1 standard deviation of the mean.
17.1 - 3.4 = 13.7
17.1 + 3.4 = 20.5
Between 13.7 miles and 20.5 miles.