In this assignment, you will use IBM SPSS to conduct a two-way factorial ANOVA using the .sav file your instructor provided. Gender, low/up (whether the students are lower or upper class students), and total score will be used as the variables.
Complete the following:
Step 1. Provide a context for the data set in the .sav file your instructor supplied. Include a definition of the specified variables, levels of each factor, and the outcome variable. Define the corresponding scales of measurement for each variable. Specify the sample size of the data set.
Step 2. Specify the research questions related to the factorial ANOVA. Articulate the null hypotheses and alternative hypotheses for Factor A, Factor B, and the A x B interaction. Specify the alpha level.
Step 3. Analyze the assumptions of the factorial ANOVA. Paste the SPSS histogram output for heart rate and discuss your visual interpretations. Paste SPSS descriptive statistics output showing skewness and kurtosis values for total score and interpret them (that is, values of 0 are perfectly normal; values between +/- 1 are ideal; values +/- 2 are acceptable; values beyond +/- 2 are a potential violation). Report the results of the Shapiro-Wilk test and Levene test and interpret them. Summarize whether or not the assumptions of the factorial ANOVA are met.
To provide context, begin by reporting the grand mean on Y, the means of Y for both main effects (A, B) and the means of the interaction (A*B). You may paste SPSS output of these descriptive statistics, but you should also report them in the narrative.
Next, paste SPSS output of the A*B cell means plot on Y. Designate Factor A on the horizontal axis and separate lines for Factor B. Provide a visual interpretation of this graph in terms of possible main effects and an interaction.
Then paste the SPSS output for the factorial ANOVA. Report the results for both main effects and the interaction, including F, degrees of freedom, the F value, the p value, a calculation of effect size, and interpretation of the effect size (calculate and report simple eta squared; do not use partial eta squared from SPSS output).
For each factor and the interaction, also report SPSS calculations of observed power and interpret them in terms of type II error.
Finally, for each factor and the interaction, interpret the results against the null hypotheses articulated in step 2.
Step 5. Discuss the conclusions of the factorial ANOVA as they relate to the research question. Conclude with an analysis of the strengths and limitations of factorial ANOVA.
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