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.

T-Test Group Statistics Std. Error Gender N Mean Std. Deviation Mean Shy, Inhibited person Male 20 2.55 999 223 Female 88 3.08 1.053 .112 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Significance Mean Std. Error Difference F Sig. df One-Sided p Two-Sided p Difference Difference Lower Upper Shy, Inhibited person Equal variances 021 885 -2.049 106 .021 043 .530 258 -1.042 -.017 assumed Equal variances not -2.119 29.402 021 043 -.530 250 -1.040 -.019 assumed Independent Samples Effect Sizes Point 95% Confidence Interval Standardizer Estimate Lower Upper Shy, Inhibited person Cohen's d 1.043 -.508 .997 -.016 Hedges' correction 1.051 -.504 -.990 -.016 Glass's delta 1.053 -.503 -.993 -.010 a. The denominator used in estimating the effect sizes. Cohen's d uses the pooled standard deviation. Hedges' correction uses the pooled standard deviation, plus a correction factor. Glass's delta uses the sample standard deviation of the control groupExample 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 Group Statistics Std. Error Gender N Mean Std. Deviation Mean Extraversion_AVG Male 20 3.1063 .76764 17165 Female 88 2.8830 .72066 07682 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Significance Mean Std. Error Difference F Sig. df One-Sided p Two-Sided p Difference Difference Lower Upper Extraversion_AVG Equal variances 029 .865 1.235 106 .110 219 22320 .18066 -.13498 58138 assumed Equal variances not 1.187 27.136 123 246 .22320 .18806 .16257 .60897 assumed Independent Samples Effect Sizes Point 95% Confidence Interval Standardizera Estimate Lower Upper Extraversion_AVG Cohen's d 72930 .306 -.182 .793 Hedges' correction .73451 .304 -.181 787 Glass's delta .72066 .310 -.179 .797 a. The denominator used in estimating the effect sizes. Cohen's d uses the pooled standard deviation. Hedges' correction uses the pooled standard deviation, plus a correction factor. Glass's delta uses the sample standard deviation of the control group