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Basic SPSS help! Watch

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    Hi all,
    Looking for a little SPSS support. Probably something incredibly trivial but we don't use SPSS frequently on our Business & Management course.

    For my research project I have gathered quantitative data from over 400 consumers with a hypothesis that different consumer clusters describe premium high-street clothing brands in different ways dependent upon their psychometric and demographic profile. Whilst I have identified 5 groups of consumers within my data, I am having a little difficulty analysing their perception. The survey used the PRECON Scale; which is a metric of 19 likert questions used to identify the extent to which factors BRAND, INVOLVEMENT, ATMOSPHERE, QUALITY and STATUS contribute towards ones perception of a premium brand.

    I have already used factor analysis to reduce the quantity of questions to the 5 variables but have come to compare the means between my consumer clusters and the factors. Subsequently, I have tried to use the raw likert question data but have a feeling that isn't the right way to do it. Any ideas?

    Got quite a tight deadline on this so would be really grateful for a little help!
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    Hmm...maybe you could do the comparisons using some kind of ANOVA? Five one-way ANOVAs? Just taking a guess!
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    Do a multifactor anova.
    Failing that, try multiple regression (simultaneous, stepwise and hierarchical)
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    Using compare means, what's the significance of R and R squared? Could either be used as a measure of relationship?
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    (Original post by liamh121)
    Using compare means, what's the significance of R and R squared? Could either be used as a measure of relationship?
    Yes they can be used as a measure of relationship (usually the variance accounted for by your predictors in a model) but are you sure that the output you're seeing this in was produced using compare means? :confused: I don't think you get this using compare means...

    If you did some kind of regression analysis that would make sense, but then with regression you're not comparing means (which is what you wanted to do unless I'm mistaken!)
 
 
 
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