A way to measure the spread of data about the mean is by using the
standard deviation. If the spread is small, the standard deviation is
small. If the spread is large, the standard deviation is large. The
proportion of the data that falls within a certain number of standard
deviations from the mean is very definite and precise with a bell shaped
curve. But what can be said about the proportion of data spread about
the mean for other distributions such as skewed, symmetric, or other
shapes? Chebyshev's Theorem will solve this problem.
The basis of
Chebyshev's Theorem is that no matter how large or small a data set is
from a population or a sample, the proportion of data that lies within k
standard deviations is at least 1 - 1/k2. For k = 2, the
proportion is 1 - 1/4 = .75. For k = 3, the proportion is 1 - 1/9 =
.889. For k = 4, the proportion is 1 - 1/16 = .938. These results mean
that at least 75% of the data must fall within 2 standard deviations
from the mean, 88.9% must fall within 3 standard deviations from the
mean, and at least 93.8% must fall within 4 standard deviations from the
mean.
Many distributions will have much greater percentages of
the data falling within specified intervals. For example, in the well
known normal distribution, which is bell shaped, 95% of the data falls
within 2 standard deviations, 99.7% falls within 3 standard deviations
from the mean, and virtually 100% falls within 4 standard deviations
from the mean.
Here's an example using Chebyshev's Theorem.
Suppose
students at a local college volunteer to work on community projects,
such as cleaning parks, renovating playgrounds, and planting trees. A
professor in charge of the program kept track of the time in hours that
each student worked. Suppose a random sample of x students in the
program were picked and the mean hours the students worked was 24.5
hours, and the standard deviation was 1.4 hours. From this information
we can find an interval which at least 75%, 88.9% and 93.8% of the
students worked.
Interval which at least 75% worked is 24.5 +/- 2(1.4) = 21.7 to 27.3 hours.
Interval which at least 88.9% worked is 24.5 +/- 3(1.4) = 20.3 to 28.7 hours.
Interval which at least 93.8% worked is 24.5 +/- 4(1.4) = 18.9 to 30.1 hours.
This guide should help students better understand Chebyshev's Theorem and how it can be applied.
No comments:
Post a Comment