1. Put the data into SPSS (data view) NOTE: you can’t enter the data as it appears below. You have to do something to make the data work in the SPSS analysis.
2. Variable view
   • name the variables
   • label the variables
   • set the number of decimal places to match the data
   • set the measure correctly
3. Use the snipping tool to paste Variable View & Data View into Microsoft Word

Step 2: SPSS Factorial ANOVA

1. Run the analysis of variance, including descriptive statistics and partial eta squared as the estimate of effect size.
   • Depending on the version of SPSS you are using, some of the required boxes to check shown in the videos linked under content will be under different tabs than the video shows. All the options are there but SPSS moves them around a bit depending on the version. For example, to get the Grand Mean, Descriptive Statistics, and Effect Size tables in some versions it is under Options and newer versions under EM Means.
   • Do ensure you have the same tables in the output that are shown in the video. If you do not then you missed something.
   • Note: no post hoc tests will be required because we will only be dealing with 2 x 2 designs.
2. Copy the entire output into Microsoft Word.

Step 3: Excel Line Graph

1. Using Microsoft Excel, create a line graph of the dependent variable means by the level of the independent variable. For the graph, you are using the Interaction mean, and sd for the four groups (IVA levels by IVB levels) are in the Descriptive Statistics table in a row with level names.
   • The description below the video showing how to graph explains where the data is in your output that you will use to make the graph.
   • Y-axis starts at 0.
   • The title both the x & y-axis based on the scenario.
   • You should not have a title above the graph.
   • Include a legend.
   • You do not have to include error bars.
2. Copy the line graph into Microsoft Word

Step 4: APA write up

1. APA format factorial ANOVA write up for the problem set, written in Microsoft Word.

Problem Set

A researcher is interested in the effects of therapy and major depression on the number of cigarette packs smoked per month in young adult smokers. Participants were recruited via a newspaper advertisement looking for 24 participants that had been diagnosed with major depression and 24 participants that had not been diagnosed with major depression.

The researcher randomly assigned half the participants from the two major depression groups [presence major depression (n = 12) & absence major depression (n = 12)] to attend group therapy once a week for 6 months. The other half of the participants from the two major depression groups [presence major depression (n = 12) & absence major depression (n = 12)] were assigned to attend individual therapy once a week for 6 months.

The researcher asked all participants to report the number of cigarette packs they smoked each month. The researcher only used in the below data the number of cigarette packs smoked for the 6 month, which was the last month of therapy for all participants. The research question: “What are the effects of type of therapy (individual or group) and diagnosis of major depression (presence or absence) on the number of cigarette packs smoked per month by young adult smokers?”

Hint: You will need ONE column for each independent variable and one column for the dependent variable (SCORES).

PresenceMDep IndTherapy	PresenceMDep GrpTherapy	AbsenceMDep GrpTherapy	AbsenceMDep IndTherapy
8 15 30 20 15 5 10 12 5 9 10 8	5 10 10 7 12 4 9 8 6 10 12 5	10 8 7 5 9 1 1 3 5 9 8 4	5 10 10 7 1 4 1 4 6 5 2 2

Answer rating: 100% (QA)

Variable View Variable Name PresenceMDep Label Presence or absence of major depression Decimals 0 Measure Nominal Variable Name IndTherapy Label Type ... View the full answer