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| is the linear relationship between 2 metric variables |
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| correlation coefficient is represented by |
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| correlation coefficient ranges |
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| for correlation coefficents the negative values |
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| as one variables increases, the other decreses |
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| correlation coefficients for positive values: |
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| as one variable increase, the other variable also increase |
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| distance from observed data point to best fit line |
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| R (squared) is the measure |
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| of how well the best fit line captures the variance |
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ordinal ad nominal medians rather than means correlation basked on ranks can also be used for interval and ratio data example is consumers relative brand preference rankings |
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| the number of independent variables measuring a construct by examining correlation between variables. |
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| factor analysis creates the thing with |
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| multi-attribute decisions. |
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| discriminant analysis predicts a categorical dependent variable from independent variables |
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| in cluster analysis subgroups should be |
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| homogeneous within and heterogeneous between the groups |
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| the groups are not pre-defined |
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| multidimensional scaling is that |
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| perceptual mapping graph. It is how people perceive products or services relative to each other. |
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| translating non-metric data into numbers. |
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| what to code for in open ended responses |
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themes magnitude and intensity |
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| coding open ended responses for themes you use |
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| one variable (one column in spreadsheet) for each common theme |
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| coding categorical responses |
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| dual choice (yes/no) questions |
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