Hello, I need help with answering these questions for this data.

• What is your research question? What is your hypothesis or prediction and why?
• The obtained result of the t-test: What is the t value, df, and the significance level? Is it statistically significant? For independent t-test, if the Levene's Test for Equality of Variance is significant (sig. value t value, df, and significance level associated with unequal variances. Also, what is the effect size as determined by the eta squared (²)?
• An interpretation of the results including the means and standard deviations.

Example independent ttest results section: The research question is whether there is a gender difference in happiness. To do this the mean happiness score of males needs to be compared with the mean score of females. It is predicted that...because... [Note: Be sure to specify exactly what you expect to nd and the reasons you have for expecting a relationship or group differences] The WTest for Equality of Variance was not signicant (p : .376) indicating the homogeneity of variance assumption was met. An independent-samples i-test based on equal variances assumed showed that there were signicant gender differences in happiness, Kali) = m, p = .xxx, 113 = .xx. OR HERE IS AN EXAMPLE FOR A NONSIGNIFICANT FINDING WITH EQUAL VARIANCES NOT ASSUMED i The W Test for Equality of Variance was signicant (p : .042) indicating a violation of the homogeneity of variance assumption. An independent-samples itest based on unequal variances showed that there was no relationship between gender and happiness, Kali) = W p = .xxx, 112 = .xx. (Note: The number in parentheses following i represents the degrees of freedom for the test. An example might b; i(42) = 21.95,p = .127, n2 = .21) The results indicated that on average females (M: m, SD = m) are happier than males (M = m, SD = m). The 112 value of .21 indicated that gender accounted for about 21% of the variability in happiness, which was a large effect. OR HERE IS A NONSIGNIFICAN T FINDING DESCRIPTION -- The mean happiness for males was mD : W and the mean for females was WISD : W. The results do not support our hypothesis and showed that males and females do not differ in level of happiness. However, the 112 value of .21 indicated that gender accounted for about 21% of the variability in happiness, which was a large effect. OR HERE IS A SIGNIFICANT FINDING DESCRIPTION THAT IS OPPOSITE OF YOUR HYPOTHESIS Although the test was signicant, the results were counter to the research hypothesis. It was the males (M: M SD = W who reported higher levels of happiness than did the females (M = m, SD = m). The 113 value of .21 indicated that gender accounted for about 21% of the variability in happiness, which was a large effect. N are {baryon needT to write in complete andformaf English, not the abbreviated variabfe nariies such as "happv \" or \"W\" we use in SPSS. Folfow ifieforrimi ofrm APA-srvfe results section. Example paired ttest results section The research question is whether GPA increases or decreases from high school to college. It is predicted that...because... [Note: Be sure to specify exactly what you expect to find and the reasons you have for expecting a relationship or differences] A paired-samples t-test showed signicant change in GPA, i(20) = 2.29, p = .033, n3 = .21. Results indicated that mean college GPA (M = 3.12, SD = .48) was signicantly lower than mean high school GPA (M = 3.35, SD = .34). Our hypothesis was 51AM and it was a large effect. OR Our hypothesis was not supported and perhaps the reason is... T-Test [DataSet] ] Paired Samples Statistics Std. Error Mean N Std. Deviation Mean Pair 1 congruent 15.05359 70 5.055185 604210 incongruent 27.56733 70 9.926461 1.186439 Paired Samples Correlations Significance N Correlation One-Sided p Two-Sided p Pair 1 congruent & incongruent 70 507 <.001 paired samples test differences significance confidence interval of the std. error difference mean deviation lower upper df one-sided p two-sided pair congruent incongruent effect sizes point standardizer estimate cohen d hedges correction a. denominator used in estimating sizes. uses sample standard difference. plus a factor>