I gather data from two different groups of students: a experimental group and a control group. The experimental group received an intervention while the other one none. I am trying to figure out what can be interpreted from those results. I heard contradictory interpretation basically one stating that the null hypothesis can be rejected, the next one the null hypothesis cannot be rejected. Here are the results:
(1) we can observe a numerical difference equal to about 2 points and a SD difference about 1 point.
(2) I understood that the t-test assume that SD is about the same.
LEVINE TEST to check equality of variance or Standard Deviation (SD)
(3) Levine test of equality variance (Ho: variance are equal, H1: variance are not equal) show a F-value F=1.434.
(4) As the ratio F (variance of the means: average of the sample variances) is greater than 1 => numerator grater than denominator => variances cannot be assumed to be equal.
(5) However, Given that p-value sig=0.240 > 0.05 , It is therefore not statistically different.
T-Test to check whether the means are statistically different
(7) T test: Ho: means are equal, H1: means are not equal.
(8) Because sig is greater than 0.05 the null hypothesis cannot be rejected.
(6) Therefore, we cannot interpret the difference in mean as statistically significant.
(7) It follows that we cannot ascertain with 95% certainty that the intervention on the students had a significant effect.
I have two questions:
(A)I am stuck with my statement for levene test (4) and (5). Many argue that you just have to look at the p-value of sig=0.240 > 0.05, therefore variance can be assumed to be equal. But the F value shows that the variance are different....?
(B) What can be interpreted from the 95% confidence interval of the difference? the lower being -4.861 and upper 1.241 ? Can I say that that there is a greater difference in means with the lower scores than the higher scores?
very long time I dealt with Stats. Very grateful for any help or insight.