Testing the Difference between Two Variances
Characteristics of the F Distribution
In addition to comparing two means, statisticians are
interested in comparing two variances or standard
deviations. For example, is the variation in the
temperatures for a certain month for two cities different?
In another situation, a researcher may be interested in
comparing the variance of the cholesterol of men with the
variance of the cholesterol of women. For the comparison of
two variances or standard deviations, an F test is used.
The F test should not be confused with the chi-square test,
which compares a single sample variance to a specific
population variance,
If two independent samples are selected from two normally
distributed populations in which the variances are equal
 12   22 and if the samples variances s12 and s 22 are compared
as s12 , the sampling distribution of the variances is called the
2
s2
F distribution.
Remember also that in tests of hypotheses using the traditional
method, these five steps should be taken:
Step 1: State the hypotheses and identify the claim.
Step 2: Compute the test value.
Step 3: Find the p-value.
Step 4: Make the decision.
Step 5: Summarize the results.
Example
A medical researcher wishes to see whether the variance of the
heart rates (in beats per minute) of smokers is different from the
variance of heart rates of people who do not smoke. Two samples
are selected, and the data are as shown. Using  =0.05, is there
enough evidence to support the claim?
Solution
Step 1 State the hypotheses and identify the claim.
Step 2 Compute the test value.
Step 3 Find the P-value. since  = 0.05 and this is a two-tailed
test. Here, d.f.N = 26 - 1 = 25, and d.f.D = 18 -1 =17.
p-value= 2*Fcdf(3.6,10^99,25,17)=2*0.0042=0.0084
Step 4 Make the decision. Reject the null hypothesis, since pvalue<0.05.
Step 5 Summarize the results. There is enough evidence to support
the claim that the variance of the heart rates of smokers and
nonsmokers is different.
Let’s Do It!
The standard deviation of the average waiting time to see a doctor
for non-life-threatening problems in the emergency room at an
urban hospital is 32 minutes. At a second hospital, the standard
deviation is 28 minutes. If a sample of 16 patients was used in the
first case and 18 in the second case, is there enough evidence to
conclude that the standard deviation of the waiting times in the first
hospital is greater than the standard deviation of the waiting times
in the second hospital?