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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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