# Homogeneity of variance and independent samples t-test

## Assess homogeneity of variance when comparing two independent groups on a continuous outcome

The assumption of homogeneity of variance is the second statistical assumption that needs to be tested when comparing two independent groups on a continuous outcome. Homogeneity of variance is assessed using Levene's Test for Equality of Variances. In order to meet the statistical assumption of homogeneity of variance, the

Homogeneity of variance essentially makes sure that the distributions of the outcomes in each group are comparable and similar. If independent groups are not similar in this regard, superfluous findings can be yielded. Independent samples t-tests should not be conducted on continuous variables that violate the assumption of homogeneity of variance. Independent samples t-tests should only be conducted on continuous outcomes between groups that have "equal" or "similar" variances.

*p*-value for Levene's Test should above .05. If Levene's Test yields a*p*-value below .05, then the statistical assumption of homogeneity of variance has been violated.Homogeneity of variance essentially makes sure that the distributions of the outcomes in each group are comparable and similar. If independent groups are not similar in this regard, superfluous findings can be yielded. Independent samples t-tests should not be conducted on continuous variables that violate the assumption of homogeneity of variance. Independent samples t-tests should only be conducted on continuous outcomes between groups that have "equal" or "similar" variances.

### The steps for assessing the assumption of homogeneity of variance in SPSS

1. Click

2. Drag the cursor over the

3. Click on

4. Click on the continuous outcome variable to highlight it.

5. Click on the

6. Click on the "grouping" variable to highlight it.

7. Click on the

8. Click on the

9. Enter the

10. Enter the

12. Click

13. Click

**.**__A__nalyze2. Drag the cursor over the

**Co**drop-down menu.__m__pare Means3. Click on

**Independen**.__t__-Samples T Test4. Click on the continuous outcome variable to highlight it.

5. Click on the

**arrow**to move the outcome variable into the**box.**__T__est Variable(s):6. Click on the "grouping" variable to highlight it.

7. Click on the

**arrow**to move the "grouping" variable into the**box.**__G__rouping Variable:8. Click on the

**button.**__D__efine Groups9. Enter the

**categorical value for the first independent group**into the**Group**box. Example:__1__:**"****0"**10. Enter the

**categorical value for the second independent group**into the**Group**box. Example:__2__:**"****1"**12. Click

**Continue**.13. Click

**OK**.### The steps for interpreting the SPSS output for homogeneity of variance

1. In the

2. In the

If it is

If the

**Group Statistics**table, there are several important pieces of information about each independent group in the "grouping" variable including the size of each group (**N**) and their respective means (**Mean**) and standard deviations (**Std. Deviation**). Disregard the**Std. Error Mean**values for practical purposes.2. In the

**Independent Samples Test**table, look under the**Levene's Test for Equality of Variance**column heading. Look at the*p*-value in the**Sig.**column.If it is

**MORE THAN .05**, then researchers have**met the assumption of homogeneity of variance and can interpret the independent samples t-test along with its means and standard deviations**from the first table.If the

*p*-value is**LESS THAN .05**, then researchers have**violated the assumption of homogeneity of variance and will use a non-parametric Mann-Whitney U**to conduct their analysis.### Was the assumption of homogeneity of variance met for independent samples t-test?

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