Question # 2: Factorial ANOVA For this exercise, you will formulate your own null and alternate hypotheses for a factorial, between-subjects design. Create your own data for a 2 x 2 Factorial Analysis of Variance. Test your own hypotheses using factorial ANOVA, Everyone needs to develop their own research question, and everyone's data and responses should be unique. The data I created, as well as the analysis can be found in the in the EacANOVA_Lunch$_Patron_Gender worksheet and is to be used as an example only. Identify a research question appropriate for factorial ANOVA analysis. For example: 2X2 Factorial ANOVA ✓ IV1: Type of Drug (Experimental vs. FDA approved) IV2: Age (under 40 vs 40+) DX: Length of Life after Cancer Diagnosis Research Question (Interaction): Do older cancer patients live longer after diagnosis if they have the experimental drug vs the approved drug. 2X2 Factorial ANOVA ✓ IV1: Brand of popcorn (Snoreville vs HollyTime) ✓ IV2: Microwave power setting (High Power vs Low Power) DV: Taste (from 1 to 10)- higher scores indicate better taste Research question (interaction) - Does microwave power setting for cooking popcorn affect taste score differently depending on the brand? Create two categorical independent variables, each with two levels. Decide on a continuous dependent variable (interval or ratio). Develop a research question for main effects and interaction. You can create any hypothetical experimental situation and choose any IVs and DV if it conforms to the guidelines for the type of variables, number of variables and number of participants. Create data (dependent variable scores) for your analysis. Your 2 x 2 ANOVA should have five (people?) in each "cell, 20 people total. Make sure that you have equal n (5) in each cell, and 20 (N) in the data set. The data you create should result in a significant interaction. Make sure the overall F value is significant for the interaction term. You will need to think carefully of what an interaction means and how to set up your numbers to create one. Look at the examples above and in the text and lecture notes. Significant main effects can be present for one IV, both IVs, or neither IV. However, you MUST have a significant interaction to interpret. L/nBelow is an example of how to arrange your data in Excel. Gender is an independent variable, as is Patron Status (Host vs Guest) at a restaurant. The dependent variable is the price of lunch ordered. Do men or women differ in the price of lunch ordered depending on whether they are the (paying) host or (not paying) guest. Gender Male Male Male Male Male Female Female Female Female Female Host 8.00 7.00 8.25 9.00 8.25 8.25 8.75 9.75 8.00 9.25 Guest 9.75 10.25 9.50 9.00 10.50 8.75 9.00 9.25 8.50 8.75 Analysis Run the ANOVA: Two Factor With Replication (DATA → DATA ANALYSIS → ANOVA: TWO FACTOR WITH REPLICATION). Include the labels when selecting the data. Create a line chart and bar chart of the cell means. Title it and label all chart elements. Questions 1. What are your research questions? State them in words. 2. Clearly state your independent variables (IVS) and their levels. Also state the dependent variable (DV). 3. What are the null and alternate hypotheses? (HINT - how many are needed?) 4. Interpret the results of the ANOVA table and answer all questions below: a. Was there a significant main effect for your first IV Did you reject the null hypothesis? Explain your response using the appropriate quantitative terms in APA style. Describe what the results mean within the context of your research question. b. Was there a significant main effect for your second IV Did you reject the null hypothesis? Explain your response using the appropriate quantitative terms in APA style. Describe what the results mean within the context of your research question. c. Was the interaction significant? Did you reject the null hypothesis? Explain your response using the appropriate quantitative terms in APA style. Describe what the results mean within the context of your research question. 5. Create two charts of the means of your four cells, a bar chart and a line chart. Use these charts to determine the specific nature of the interaction. 6. Compute, report and interpret omega squared for the interaction. What does it mean in the context of your analysis?

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Question # 2: Factorial ANOVA For this exercise, you will formulate your own null and alternate hypotheses for a factorial, between-subjects design. Create your own data for a 2 x 2 Factorial Analysis of Variance. Test your own hypotheses using factorial ANOVA, Everyone needs to develop their own research question, and