Hello, I need help with answering these questions for this two-way ANOVA.

Questions:

What is your research question? What is your hypothesis or prediction and Why? The obtained result of the ANOVAs: What is the F value, df and the signicance level? Is it statistically signicant? What is the effect size as determined by the eta squared (113) value? For the two-way ANOVA, be sure to report the F values for two main effects and one interaction. If the F test was signicant, what is the result of the posthoe analysis? If the Levene's Test is signicant (indicating a violation of the homogeneity of variance assumption), be sure to report the appropriate post hoc test associated with unequal variances for the one- Way AN OVA. An interpretation of the results including the means and standard deviations. For the two-way ANOVA results, create an APA style table showing the sample sizes, means and standard deviations (from the W table in your SPSS output). L) Example results section of Two-Way ANOVA: The research question is whether marital status and gender are related to family life satisfaction. A 3 X 2 ANOVA showed no signicant interaction between marital status and gender, F (2, 194) = 0.06, p = .939, partial n3 = .12, and no signicant main effect of gender on family life satisfaction, F (l, 194) = 2.72, p = .101, partial n3 = .05. There was a signicant main effect for marital status, F (2, 194) = 4.66, p = .011, partial n3 = .26. Levene's statistic was not signicant indicating the equal variance assumption was met. Tukey HSD posthoe analysis revealed that those who are married reported higher levels of family life satisfaction than those who are single or cohabitating. The means and standard deviations for family life satisfaction by gender and marital status are presented in Table 1 [create an APA style table of descriptive statistics]. OR HERE IS AN EXAIVEPLE FOR A SIGNIFICANT INTERACTION Significant interaction was found between marital status and gender [report the relevant F statistics]. Follow up tests will need to be conducted to evaluate the differences in the means among levels of one factor for each level of another factor. Univariate Analysis of Variance Between-Subjects Factors Value Label N Liking of Sports Like 49 Dislike 13 W Don't Care 46 Likes to Travel Like 93 N Dislike 5 W Don't Care 10 Descriptive Statistics Dependent Variable: Full of Energy Liking of Sports Likes to Travel Mean Std. Deviation N Like Like 2.88 905 43 Dislike 4.50 707 2 Don't Care 2.75 500 4 Total 2.94 922 49 Dislike Like 2.89 1.269 9 Dislike 5.00 1 Don't Care 2.00 1.000 3 Total 2.85 1.345 13 Don't Care Like 2.93 1.010 41 Dislike 3.00 2.828 2 Don't Care 2.33 577 3 Total 2.89 1.059 46 Total Like 2.90 979 93 Dislike 4.00 1.732 5 Don't Care 2.40 699 10 Total 2.91 1.028 108Levene's Test of Equality of Error Variancesa,b Levene Statistic df1 df2 Sig. Full of Energy Based on Mean 2.084 7 99 052 Based on Median 2.010 99 061 Based on Median and 2.010 95.370 062 with adjusted df Based on trimmed mean 2.086 7 99 052 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Dependent variable: Full of Energy b. Design: Intercept + sport1 a + travel1d + sport1 a * travel1 d Tests of Between-Subjects Effects Dependent Variable: Full of Energy Type Ill Sum Partial Eta Source of Squares df Mean Square F Sig. Squared Corrected Model 13.069 8 1.634 .617 129 116 Intercept 260.099 260.099 257.486 <.001 sport1 a in travel1 d error total corrected a. r squared=".116" estimated marginal means liking of sports dependent variable: full energy confidence interval mean std. lower bound upper like dislike don care .310 likes to travel .321 .157 hoc tests multiple comparisons tukey hsd difference j sig. ..65 .84 .54 .09 .71 .05 .206 .44 based on observed the term is square homogeneous subsets hsda.b.c subset n for groups are displayed. means. uses harmonic sample size="25.195" b. group sizes unequal. used. type levels not guaranteed. c. alpha=".05.Profile" plots>