Ψ420AinsworthLab #4Using a data set similar to one in Chapter 5, question 5.1 pg. 241 (but the Y values are different). This is ratings of cleanliness as a result of fabric type (A) by presoak time (B).1. Set up the data set as seen on the last page:a. In variable view:i. Name the first variable fabric, decimals -> 0, values -> 1 = cotton and 2 = polyester, label -> “Type of Fabric”.ii. Name the second variable presoak, decimals -> 0, values -> 1 = 5 min, 2 = 10 min, 3 = 15 and 4 = 20, label -> “Amount of Presoak Time in Minutes”.iii. Name the third variable y, decimals -> 0, label -> “Rating of Cleanliness”b. Back in Data View:i. Enter in the values as seen on the last page (ignore the first three columns they are just there to help keep track of the AB combinations as well as the subjects).2. In SPSS:a. Perform a factorial ANOVA using this syntax (you’ll have to type it):UNIANOVA y BY fabric presoak /CONTRAST (presoak) = special (-3 -1 1 3 1 -1 -1 1 -1 3 -3 1) /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /POSTHOC = fabric presoak ( TUKEY ) /PLOT = PROFILE( presoak*fabric ) /PRINT = DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = fabric presoak fabric*presoak .b. Annotate the output3. By hand:a. Perform a traditional computational approach. Include a homogeneity test, partial eta-squared, partial omega-squared, and Tukey tests of all pairsof presoak groups.b. Perform the same ANOVA through regression using trend coefficients for presoak time. Set up the columns, perform the ANOVA and test all comparisons as planned.4. Write a short result section of the SPSS ANOVA. Make sure to include everything in the analysis in the write up and explain the interaction.Ψ420AinsworthDATAfabric presoak y1 1 1 2a1b1 2 1 1 63 1 1 64 2 1 6a2b1 5 2 1 56 2 1 37 1 2 7a1b2 8 1 2 99 1 2 910 2 2 5a2b2 11 2 2 712 2 2 513 1 3 8a1b3 14 1 3 1115 1 3 916 2 3 9a2b3 17 2 3 618 2 3 1219 1 4 6a1b4 20 1 4 721 1 4 422 2 4 12a2b4 23 2 4 1024 2 4
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