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Predicting Innovativeness with Multiple Correlation TechniquesSo far in this chapter, we have looked only at two-variable generalizations, each consisting of an independent variable (a characteristic of adopter categories) that is related to the dependent variable of innovativeness. The resulting generalizations somewhat oversimplify reality, of course, by treating each independent variable separately in it is relationship to innovativeness. Many of the independent variables are interrelated with each other, as well as with innovativeness. For instance, education and social status are both positively related to innovativeness (Generalizations 7-3 and 7-5), but education and social status are also positively related with each other. Statistical techniques like multiple correlation allow us to determine how much of the variance in innovativeness is uniquely explained by its co-variance with education, while removing the co-variance of both innovativeness and education with social status (and other independent variables).
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