When to use a t Test - Two Sample Assuming Equal Variances
In the constant quest to reduce variation and improve products,
companies need to evaluate different alternatives. A t test using
two samples compares two sets of test data. It helps determine
if the means (i.e., averages) are the same or different from each
other. Excel offers several two sample t tests:
If data sets are independent of each other
If data sets are dependent on each other: when natural pairs
of observations exist (e.g., using the same operator on a machine
while comparing two different modes of operation.)
Consider the following example.
t test two sample
If you're producing rubber made with two different recipes, you
might want to know if the tensile strengths are the same or different
(Juran's QC Handbook 4th pg 23.74):
Define the null and alternate Hypothesis
Conduct the Test
Now, conduct a test and enter the data into Excel:

Conduct an F test to determine if variances are equal
Since the two recipes aren't "paired" or dependent in
any way, the first step is to determine if the variances are equal
to determine which t test to use. So, select the data with the mouse
and click on the QI Macros Menu to select the F test:

The QI Macros will prompt for a significance level (default = 0.05):

The f test macro will calculate the results:

Interpreting the F test results
|
If
|
Then
|
test statistic > critical value
(i.e. F > F crit) |
Reject the null hypothesis |
test statistic < critical value
(i.e. F < F crit) |
Accept the null hypothesis |
| p value < a |
Reject the null hypothesis |
| p value > a |
Accept the null hypothesis |
Since F < Fcrit (3.05567 < 6.38823) and p value > a
( .15241 > 0.05, we can accept the null hypothesis that the
variances are equal. Now we can run the t test assuming equal variances.
Run t test Assuming Equal Variances
Now, select the data with the mouse and click on the QI Macros
Menu to select the two sample t test:

The QI Macros will prompt for a significance level (default = 0.95)
and hypothesized difference in the means:

The t test two sample assuming equal variances macro will calculate
the results:

Interpreting the t test two sample results
|
If
|
Then
|
test statistic > critical value
(i.e. t> tcrit) |
Reject the null hypothesis |
test statistic < critical value
(i.e. t< tcrit) |
Accept the null hypothesis |
| p value < a |
Reject the null hypothesis |
| p value > a |
Accept the null hypothesis |
Since the null hypothesis is that the mean difference (1-x2) =
0, this is a two-sided test. Therefore, use the two-tail values
for your analysis.
Since the t statistic < t critical (.23727< 2.30601) and
p value > a ( .81841> 0.05)
, we can accept the null hypothesis that the means are the same.
Therefore we can say that the two recipes produce rubber with the
same mean tensile strength at a 95% confidence level.
Excel Note:
Notice that both the F and t test results reversed the order of
the recipes. For some unknown reason Excel requires the recipes
with the largest variance and mean to be first to ensure correct
calculations. The QI Macros reorganizes your data to ensure Excel
performs the calculations correctly.
The t test - two sample assuming equal variances test is just one
of the tests included in the QI Macros Statistical
Process Control software. Other tests include:
Download
the FREE 30-day Evaluation copy of the QI Macros Excel SPC Software for Six Sigma
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