Two-Sample F-Test for Population Variances |
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Introduction
The aim of this test is to compare two population variances, and
, based on two independent random samples,
and
, of size
and
, respectively.
Method
The following method assumes that the two independent random samples, and
, of size
and
, respectively, come from two normally distributed populations,
and
.
F-Test
If the samples under consideration are normally distributed in their respective populations, then the sample statistic,
,
has an F-distribution with degrees of freedom for the numerator, and
degrees of freedom for the denominator, where
and
are the unbiased sample variances. If the population variances,
and
, are assumed equal, then the sample statistic,
,
has also an F-distribution with and
degrees of freedom.
Hypotheses
The null hypothesis takes the form , with the following alternative hypotheses:
§ | ![]() |
§ | ![]() |
§ | ![]() |
Refer to Alternative Hypothesis for additional information of this subject.
Output Format
Two-Sample: |
<The two-Sample Number> |
|
Sample: |
1 |
2 |
Observations: |
<Observations in Sample> |
<Observations in Sample> |
Sample Mean: |
<The Sample Mean> |
<The Sample Mean> |
Sample Variance: |
<The Sample Variance> |
<The Sample Variance> |
Degrees of Freedom: |
<Degrees of Freedom> |
<Degrees of Freedom> |
Significance Level: |
<The Significance Level> |
|
F: |
<F> |
|
Left-Tailed P(F): |
<The Left-Tailed P-Value of F> |
|
Left-Tailed F Critical: |
<The Left-Tailed Critical Point> |
|
Left-Tailed Test: |
"[Do not ]Reject Ho" |
|
Right-Tailed P(F): |
<The Right-Tailed P-Value of F> |
|
Right-Tailed F Critical: |
<The Right-Tailed Critical Point> |
|
Right-Tailed Test: |
"[Do not ]Reject Ho" |
|
Two-Tailed (Left) 2P(F): |
<Two-Tailed Left P-Value of F, doubled> |
|
Two-Tailed (Right) 2P(F): |
<Two-Tailed Right P-Value of F, doubled> |
|
Two-Tailed (Left) F Critical: |
<Two-Tailed Left Critical Point> |
|
Two-Tailed (Right) F Critical: |
<Two-Tailed Right Critical Point> |
|
Two-Tailed Test: |
"[Do not ]Reject Ho" |
|