Psychology 320 SPSS Assignment #6: Part 1 Name Today we will begin by using SPSS Statistical Software to compute a factorial ANOVA! "Download or open the class data file from Canvas and open it with SPSS. We want to test whether there are effects of transfer student status and whether you are a first generation student (FGS; whether your parents attended college) on the number of hours per week you work at a job (as well as whether the effect of FGS status on hours worked depends on transfer status). To do this, we'll use a factorial ANOVA. Why is factorial ANOVA the correct test to use for this question? To compute the factorial ANOVA, choose "analyze", "general linear model", "univariate". Place the independent variables in the box labeled "fixed factors". Which variables are these? Place the dependent variable in the dependent variable box. Which variable is this? Click on 'EM Means' and in the top box, you want to ask for the means for both main effects ("Transfer" and "ParentEducation") and also check off 'compare main effects'. Click continue, and ok. Remember, we're looking for an F test for each main effect and the interaction. Based on the output, what is the value of the: F for Transfer Degrees of Freedom Between Degrees of Freedom Within_ p value Based on the p value, should we reject the null hypothesis? _ F for Parent Education Degrees of Freedom Between Degrees of Freedom Within P value Based on the p value, should we reject the null hypothesis? F for the interaction. Degrees of Freedom Between Degrees of Freedom Within_ p value Based on the p value, should we reject the null hypothesis? To interpret the interaction, we need to look at a graph. To graph the interaction, click on 'plots' in your general linear model window. Drag Parent Education to the horizontal axis, and Transfer to 'separate lines'. Click add, and continue. Draw the graph here: How would you interpret the interaction (in a sentence or two) based on that graph? Write your full conclusion here, based on the results above (effects of gender, relationship, and the interaction - whether each was significant)