Statistics - 3.2 Measures of Dispersion
Chebyshev's Inequality
For any data set or distribution, at least (1 - 1/k^2)=100% of the obserationslie within k standard deviations of the mean, where k is any number greater than 1.
In a statistics class, the standard deviation of the heights of all students was 3.9 inches. The standard deviation of the heights of males was 3.4 inches and the standard deviation of females was 3.3 inches. Why is the standard deviation of the entire class more than the standard deviation of the males and females considered separately?
The standard deviation of the entire class is more than the standard deviation of the males and females considered separately because the distribution of the entire class has more dispersion.
True or False: When comparing two populations, the larger the standard deviation, the more dispersion the distribution has, provided that the variable of interest from the two populations has the same unit of measure.
True, because the standard deviation describes how far, on average, each observation is from the typical value. A larger standard deviation means that observations are more distant from the typical value, and therefore, more dispersed.
True or False: Chebyshev's inequality applies to all distributions regardless of shape, but the empirical rule holds only for distributions that are bell shaped.
True, Chebyshev's inequality is less precise than the empirical rule but will work for any distribution, while the empirical rule only works for bell-shaped distributions.
The sum of the deviations about the mean always equals
Zero
Empirical Rule
If data have a distribution that is bell shaped, the Emperical Rule can be used to determine the percentage of data that will lie within k standard deviations of the mean. (pg 139)
The standard deviation is used in conjunction with the ______ to numerically describe distributions that are bell shaped. The ______ measures the center of the distribution, while the standard deviation measures the ______ of the distribution.
mean, mean, spread