Exam 24: Multivariate Statistical Analysis

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List the steps in interpreting a multiple regression model.

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Nominal and ordinal scales are referred to as nonmetric scales.

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If a researcher wants to know how strongly a measured variable is correlated with a factor, what should she look at?

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A multivariate interdependence technique that classifies individuals or objects into a small number of mutually exclusive and exhaustive groups is _____.

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_____ in regression analysis refers to how strongly interrelated the independent variables in a model are.

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Multicollinearity in regression analysis refers to how strongly interrelated the independent variables in a model are.

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Which of the following is computed by most regression programs and provide an indication of how much multicollinearity exists among a set of independent variables?

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Which of the following suggests problems with multicollinearity?

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In the following formula, k stands for: In the following formula, k stands for:

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Explain how cluster analysis can identify market segments.

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An indication of how strongly a measured variable is correlated with a factor is given by the _____.

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Which analysis is portrayed by the equation: Y = bo + b1X1 + b2X2 + b3X3... + bnXn?

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_____ is the extent to which independent variables in a multiple regression analysis are correlated with each other.

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A value of R2 = 0.40 means that _____ percent of the variance in the dependent variable is explained by the independent variables.

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In discriminant analysis, a linear combination of independent variables that explains group memberships is known as a(n) _____.

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When an analysis studies the effect of several independent variables on a single dependent variable that is interval-scaled, this is called ______ analysis.

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Explain why and how a business researcher uses factor analysis.

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A ______ variable has two distinct levels that are coded as 0 and 1.

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Which of the following is a measure of the percentage of a variable's variance that is explained by the factors in factor analysis?

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Discriminant analysis predicts a categorical dependent variable based on a linear combination of independent variables.

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