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Dec 8, 2015 10:26 PM
(4671 views)

1 ACCEPTED SOLUTION

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Dec 9, 2015 6:37 AM
(7408 views)

Solution

The interactive solution is to:

Open each data table and add a new column called "Set". Rt mouse click on the column header and choose "Column Information". Change the Modeling Type to "Nominal". Then, under the Initialize Data selections, choose "Constant". Inter in a "1" for the first set, a "2" for the second set, etc.

Once all 10 sets have been modified, then go to Tables==>Concatenation. This platform will allow you to put all of the sets together.

When all of the sets are together, then go to . Analyze==>Fit Y by X. Select your measurement variable as the Y Response and the column "Set" as the X Factor.

Using the options under the red triangles in the displayed output, you can select "Means/Anova" and "Compare Means" to get the analyses you want

Jim

1 REPLY

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Dec 9, 2015 6:37 AM
(7409 views)

The interactive solution is to:

Open each data table and add a new column called "Set". Rt mouse click on the column header and choose "Column Information". Change the Modeling Type to "Nominal". Then, under the Initialize Data selections, choose "Constant". Inter in a "1" for the first set, a "2" for the second set, etc.

Once all 10 sets have been modified, then go to Tables==>Concatenation. This platform will allow you to put all of the sets together.

When all of the sets are together, then go to . Analyze==>Fit Y by X. Select your measurement variable as the Y Response and the column "Set" as the X Factor.

Using the options under the red triangles in the displayed output, you can select "Means/Anova" and "Compare Means" to get the analyses you want

Jim