Levene's Test for Equality of Variances	t-test for Equality of Means
F	Sig.	t	df	Significance	Mean Difference
One-Sided p	Two-Sided p
Forgiveness Scale	Equal variances assumed	9.010	.003	2.082	1293	.019	.038	.78563
Equal variances not assumed			2.062	1200.054	.020	.039	.78563

	t-test for Equality of Means
Std. Error Difference	95% Confidence Interval of the Difference
Lower	Upper
Forgiveness Scale	Equal variances assumed	.37738	.04528	1.52598
Equal variances not assumed	.38098	.03816	1.53310

MY QUESTION: In looking at the information in the Tables above, I have a question about the Assumption of Homogeneity when conducting a an independent-samples t-test. I am putting my thoughts below to see if I am making the right conclusions about the assumption for homogeneity. I conducted an independent-samples t-test to determine if the null hypothesis is to be rejected.

Research Question: To what degree, if any, is there a difference in the forgiveness level between the gender groups of male and female?

H₁: There is no significant difference in forgiveness between the two gender groups.

H₀: There is a significant difference in forgiveness between the two gender groups.

1. Because there is a statistical significance of .003, we cannot assume that there is an equal variance between the two genders.

2. I can assume that there is not equal variance. If the p-value of the hypothesis test is less than some significance level (e.g. = .05), then I can reject the null hypothesis and conclude that there is sufficient evidence to say that the alternative hypothesis is true. In my example, the p-value of the hypothesis test is less than some significance level (e.g. = .05) - 0.39 (two sided-p) , then I can reject the null hypothesis and conclude that there is sufficient evidence to say that the alternative hypothesis is true.

SO MY QUESTION IS: What other conclusions can I draw?

Is the assumption of homogeneity of variance proven to be false?