What is the difference between Chebyshev's Theorem and the Empirical Rule?
A) The empirical rule applies to all data sets, whether their distributions are symmetric and bell-shaped or not.
B) Chebyshev's theorem applies to all data sets except those that have approximately a symmetric and bell-shaped distribution.
C) The empirical rule applies to all data sets, whereas Chebyshev's theorem is appropriate when the data have approximately a symmetric and bell-shaped distribution.
D) Chebyshev's theorem applies to all data sets, whereas the empirical rule is only appropriate when the data have approximately a symmetric and bell-shaped distribution.

Question

Quizplus · Accepted Answer

Chebyshev's theorem is applicable to any data set, regardless of its distribution shape, providing a minimum proportion of observations within a certain number of standard deviations from the mean. The empirical rule, on the other hand, specifically applies to data sets with a distribution that is approximately symmetric and bell-shaped, detailing the percentage of data within one, two, and three standard deviations from the mean.

What Is the Difference Between Chebyshev's Theorem and the Empirical