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Annotated SPSS Output
This page shows an example of a discriminant analysis in SPSS with footnotes explaining the output. The data used in this example are from a data file, discrim.sav, with 244 observations on four variables. The variables include three continuous, numeric variables (outdoor, social and conservative) and one categorical variable (job) with three levels: 1) customer service, 2) mechanic and 3) dispatcher.
We are interested in the relationship between the three continuous variables and our categorical variable. Specifically, we would like to know how many dimensions we would need to express this relationship. Using this relationship, we can predict a classification based on the continuous variables or assess how well the continuous variables separate the categories in the classification. We will be discussing the degree to which the continuous variables can be used to discriminate between the groups. Some options for visualizing what occurs in discriminant analysis can be found in the Discriminant Analysis Data Analysis Example.
To start, we can examine the overall means of the continuous variables.
variables=outdoor social conservative
/statistics=mean stddev min max .
We are interested in how job relates to outdoor, social and conservative. Let's look at summary statistics of these three continuous variables for each job category.
tables=outdoor social conservative by job
/cells mean count stddev .
From this output, we can see that some of the means of outdoor, social and conservative differ noticeably from group...
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