# Levene's Test for Equality of Variance

• maccaman
In summary, the F statistic is a measure of the variability of the data, and is good when the variances are likely to be equal. The Sig statistic indicates the probability that the variances are equal, and is high in your case indicating that the variances are most likely equal.
maccaman
I have just started University and we have been doing t-tests however in our Computer labs we are supposed to do the Levenes Test. I have done the levenes test from our data of males and female heights in our class. i was just wondering what a value of F = 0.001 and Sig. 0.982 would mean. the computer program we are using is SPSS. I know its about testing if the variances are the same, however i don't know what the values are telling me. Any help would be greatly appreciated.

maccaman said:
I have just started University and we have been doing t-tests however in our Computer labs we are supposed to do the Levenes Test. I have done the levenes test from our data of males and female heights in our class. i was just wondering what a value of F = 0.001 and Sig. 0.982 would mean. the computer program we are using is SPSS. I know its about testing if the variances are the same, however i don't know what the values are telling me. Any help would be greatly appreciated.
Statistical tests usually involve making various assumptions about the characteristics and parameters of the population being sampled. In your case, you are performing the "t-test" to test hypotheses about 2 sampled groups. One of the assumptions made by the standard "t-test" is that the 2 populations being sampled have EQUAL VARIANCES. The purpose of the Levenes Test is to test and verify that this equal variance assumption is reasonable.

The Levenes Test outputs 2 parameters in SPSS. The first is the F statistic value. The larger the F statistic number, the greater is the possibility the variances are different. Similarly, the smaller the F value, the greater is the probability that the variances are equal. In your case, F appears very small (which is good ).

The probability that the variances are equal are reported in the value labeled "Sig", which stands for "significance". This number is a probability between 0 and 1, and the closer it is to 1, the greater is the probability the variances are equal. In your case, the "Sig" value (0.982) is very high and indicates a high probability the population variances are equal. Knowing this, you can now use the standard parametric "t-test" (which makes the assumption of equal variances) with confidence that the variances are most likely equal.

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Hi
Im a lil confused here.. the thing is I am getting no F value in my SPSS output. Like the the F value area is blank. What do i do?

## 1. What is Levene's Test for Equality of Variance?

Levene's Test for Equality of Variance is a statistical test used to determine if the variances of two or more groups are equal. It is commonly used in the field of statistics to assess the assumption of equal variances in analysis of variance (ANOVA) and other statistical tests.

## 2. Why is it important to test for equality of variance?

It is important to test for equality of variance because many statistical tests, such as ANOVA, assume that the variances of the groups being compared are equal. If this assumption is violated, it can lead to incorrect conclusions and inaccurate results. Therefore, it is necessary to check for equality of variance before performing these tests.

## 3. How is Levene's Test for Equality of Variance performed?

Levene's Test for Equality of Variance is performed by calculating the absolute deviations from the group means and then using these deviations to calculate a test statistic. This test statistic is then compared to a critical value from the F-distribution to determine if the variances are significantly different.

## 4. What are the assumptions of Levene's Test for Equality of Variance?

The assumptions of Levene's Test for Equality of Variance include: 1) the data is normally distributed within each group, 2) the data is independent, and 3) the variances are homogeneous (equal) across groups. Violation of these assumptions can lead to inaccurate results.

## 5. What are the possible outcomes of Levene's Test for Equality of Variance?

The possible outcomes of Levene's Test for Equality of Variance are: 1) if the test statistic is less than the critical value, the variances are considered equal, 2) if the test statistic is greater than the critical value, the variances are considered unequal, and 3) if the p-value is less than the chosen significance level, the null hypothesis of equal variances can be rejected.

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