Summary: This module provides an overview of hypothesis testing in situations where there are both two independent population means and known population standard deviations in statistics.
Even though this situation is not likely (knowing the population standard
deviations is not likely because usually you have two sets of data), the following
example illustrates hypothesis testing for independent means, known population
standard deviations. The distribution is Normal and is for the difference of sample
means,
independent groups, population standard deviations known: The mean lasting time of 2 competing floor waxes is to be compared. Twenty floors are randomly assigned to test each wax. The following table is the result.
| Wax | Sample Mean Number of Months Floor Wax Last | Population Standard Deviation |
|---|---|---|
| 1 | 3 | 0.33 |
| 2 | 2.9 | 0.36 |
Does the data indicate that wax 1 is more effective than wax 2? Test at a 5% level of significance.
This is a test of two independent groups, two population means, population standard deviations known.
Random Variable:
The words "is more effective" says that
wax 1 lasts longer than wax 2, on the
average. "Longer" is a
Distribution for the test: The population standard deviations are known so the distribution is normal. Using the formula above, the distribution is:
Since
Calculate the p-value using the normal distribution: p-value = 0.1799
Graph:
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Compare α and the p-value:
Make a decision: Since
Conclusion: At the 5% level of significance, from the sample data, there is not sufficient evidence to conclude that wax 1 lasts longer (wax 1 is more effective) than wax 2.
STAT. Arrow over to TESTS and press
3:2-SampZTest. Arrow over to Stats and press ENTER. Arrow down and
enter .33 for sigma1, .36 for sigma2, 3 for the first sample mean, 20 for n1, 2.9
for the second sample mean, and 20 for n2. Arrow down to ENTER. Arrow down to Calculate and press ENTER. The
p-value is p = 0.1799 and the test statistic is 0.9157. Do the procedure again
but instead of Calculate do Draw.
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