Looking at the output above, what is the significance of each of the main effects? How do you know? Of the interaction effect? How do you know? How does the result for the interaction effect influence your interpretation of the results? What is your interpretation of the results?

Use the following output, based on Field's "Goggles say" data set, to answer question 4. The independent variables are Sex (F, M) and Alcohol Consumption (None, 2 Pints, 4 Pints). Dependent variable is perceived attractiveness of date. The researcher was concerned with the effect of alcohol consumption on perceived attractiveness of date. A Factorial ANOVA was conducted on the data and the SPSS output is below. Tests of Between-Subjects Effects Dependent Variable: Attractiveness of Date Type Ill Sum of Source Squares df Mean Square Sig. Corrected Model 5479.167a 1095.833 13. 197 00 Intercept 163333.333 163333.333 1967.025 000 Sex 168.750 168.750 2.032 161 Alcohol 3332.292 1666. 146 20.065 000 N N Sex *Alcohol 1978.125 156.938 1.89 .252 Error 3487.500 42 83.036 Total 172300.00 48 Corrected Total 8966.667 47 a. R Squared = .611 (Adjusted R Squared = .565) 1. Sex Dependent Variable: Attractiveness of Date 95% Confidence Interval Sex Mean Std. Error Lower Bound Upper Bound Male 56.458 1.860 52.705 60.212 Female 60.208 1.860 56.455 63.962 2. Alcohol Consumption Dependent Variable: Attractiveness of Date 95% Confidence Interval Alcohol Consumption Mean Std. Error Lower Bound Upper Bound None 63.750 2.278 59.153 68.347 2 Pints 64.688 2.278 60.090 69.285 4 Pints 46.562 2.278 41.965 51. 160