## Visual display task - NEW

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Bartyboy
Posts: 13
Joined: Mon Apr 07, 2014 10:59 am

### Visual display task - NEW

Hey guys,

I managed to get some results on my own.

This are my steps I followed;

Recoded every series of words in either functional or luxury (= functioneel or luxe)
Then I assigned in column values:
code 1 = functioneel
code 2 = luxe

Then I executed a frequency count. You can now see how many times someone wrote down solely functional products and when they wrote down at least 1 luxury product.

Remarks:

1) I can do this for all 10 displays... but at the end I need to compare if condition 1 (first 50 participants) chose significantly LESS luxury products than condition 2 (last 50 participants). The variables I work with are nominal, and for a T-test you need numeric variables ...

2) I do see the counts: 47 functional and 53 luxury via frequency. But I need to create a variable containing this information to work with (nurmeric) so that I can compare those between my condition 1 en 2 ( via independent T-test). How do I do this ???

3) How do I aggregate the counts of 10 displays, to get to an overall number of functional and luxury across the 10 displays ??
Which I need then compare between conditions 1 & 2.

This is crosstab for Display 1 out of 10.
I want to achieve this crosstab for ALL 10 displays at once. So I'll have to aggregate somehow the 10 displays and then compute a crosstab, to see if luxury is prefered on an overall basis.. Simply speaking: I need 1 single crosstab that displays this information for all 10 displays. Does someone know how ?

Spss Statistics 20, Visa Windows, 22 age, University of Ghent, Applied Economics, ...
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GerineL
Moderator
Posts: 1477
Joined: Tue Jun 10, 2008 4:50 pm

### Re: Visual display task - NEW

Ok, so you have 100 participants, 50 of whom are in condition 1 and 50 are in condition 2.

They all have a variable that holds either a 1 or a 2 (meaning functional or luxary). This is 1 variable. correct?

In that case, you can use chi square, this is an option under crosstabs.
This compares expected count with observed count.

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