Whenever a statistical population can be described, at least roughly, by the perfectly symmetrical, bell-shaped normal curve, we can estimate the percentages of all population values that lie within specified numbers of standard deviations from the mean with the help of:

A) Tchebysheff's Theorem
B) the empirical rule
C) the interquartile range
D) box plot
E) none of these

Empirical Rule

The empirical rule, also known as the 68-95-99.7 rule, states that for a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, 95% within two, and 99.7% within three.

Normal Curve

A symmetrical, bell-shaped curve that represents the distribution of values, deviations, or probabilities for a set of data in which most measurements cluster around the mean.

Bell-Shaped

A bell-shaped curve is a graph of a distribution that resembles the shape of a bell, typically representing a normal distribution in which the bulk of the values lie towards the center and taper off symmetrically towards the extremes.