Walk-through The purpose was to compare depression levels of traditionally aged men and women college students.Psyc451: ANCOVA Lab Walk-through The purpose was to compare depression levels of traditionally aged men and women college students.Open the clinical_ancova.sav data set and select only those with a value of “1” on the “group” variable.Even as we were about to compare the mean depression of these two groups using an ANOVA, one of the research team members reminded us that there are gender differences on several variables that relate to depression, including social support, loneliness & stress,. Gender differences on these variables, she pointed out, might be “distorting” out gender comparison. Run an ANOVA comparing men and women on depression (BDI)and each of the suggested “control” variables.Variable men’s mean (std) women’s mean (std) F df MSe pDepression __________(_____) __________(_____) ________ _____, _______ __________ ______SOSS __________(_____) __________(_____) ________ _____, _______ __________ ______FRSS __________(_____) __________(_____) ________ _____, _______ __________ ______RULS __________(_____) __________(_____) ________ _____, _______ __________ ______Stress __________(_____) __________(_____) ________ _____, _______ __________ ______From the ANOVA’s…a. Is there a gender difference on depression for these groups?b. Might any of these other variables be “distorting this comparison”? Which ones? Explain your answers.c. Run a separate ANCOVA using each of these variables as the single covariate. Note which give “a different answer” then the original (gender & depression) ANOVA. Corrected means for Depression Tests of the “corrected Gender effect”covariate men’s mean (std) women’s mean (std) F df MSe pSOSS __________(_____) __________(_____) ________ _____, _______ __________ ______FRSS __________(_____) __________(_____) ________ _____, _______ __________ ______RULS __________(_____) __________(_____) ________ _____, _______ __________ ______Stress __________(_____) __________(_____) ________ _____, _______ __________ ______g. Run a single ANCOVA with all of these variables as covariatesCorrected means for Depression Tests of the “corrected Gender effect”men’s mean (std) women’s mean (std) F df MSe pdepression __________(_____) __________(_____) ________ _____, _______ __________ ______h. Is there a gender difference on depression after controlling for these variables? i. What should you be worried about when treating these ANCOVA results as “definitive”???Your Turn #1Repeat this analysis using the group=2 (no traditionally aged students) -- adding age and self esteem to the list of covariates.men’s mean (std) women’s mean (std) F df MSe pDepression __________(_____) __________(_____) ________ _____, _______ __________ ______Depression __________(_____) __________(_____) ________ _____, _______ __________ ______SOSS __________(_____) __________(_____) ________ _____, _______ __________ ______FRSS __________(_____) __________(_____) ________ _____, _______ __________ ______RULS __________(_____) __________(_____) ________ _____, _______ __________ ______Stress __________(_____) __________(_____) ________ _____, _______ __________ ______Age __________(_____) __________(_____) ________ _____, _______ __________ ______SES __________(_____) __________(_____) ________ _____, _______ __________ ______From the ANOVA’s…a. Is there a gender difference on depression for these groups?b. Might any of these other variables be “distorting this comparison”? Which ones? Explain your answers.c. Run a separate ANCOVA using each of these variables as the single covariate. Note which give “a different answer” then the original (gender & depression) ANOVA. Corrected means for Depression Tests of the “corrected Gender effect”covariate men’s mean (std) women’s mean (std) F df MSe pSOSS __________(_____) __________(_____) ________ _____, _______ __________ ______FRSS __________(_____) __________(_____) ________ _____, _______ __________ ______RULS __________(_____) __________(_____) ________ _____, _______ __________ ______Stress __________(_____) __________(_____) ________ _____, _______ __________ ______Age __________(_____) __________(_____) ________ _____, _______ __________ ______SES __________(_____) __________(_____) ________ _____, _______ __________ ______d. Run a single ANCOVA with all of these variables as covariatesCorrected means for Depression Tests of the “corrected Gender effect”men’s mean (std) women’s mean (std) F df MSe pdepression __________(_____) __________(_____) ________ _____, _______ __________ ______e. Is there a gender difference on depression after controlling for these variables? f. Any nagging doubts???Your Turn #2Please compare married and single folks on depressiona. Select only those who are married or single (I used marital < 3) in the “IF” window).b. Get the ANOVA comparing these groups on depression. Is there a difference?c. Pick 5 other variables in the data set that you think you might ought to include as covariates in a multivariate analysis of this group differences.d. Use each in a separate ANCOVA – which “change the story”?e. Use them together in a single ANCOVA – What is your “conclusion” based on the multivariate model?f. Any nagging doubts???Binary & Quantitative Variables & their Interaction data  ancova_data.savBinary/quant walk throughHere are data from a 2-condition between subjects design.