Which of the following is true of relationships between variables?A. A curvilinear relationship is much simpler to work with than a linear relationship.B. Marketers are often interested in describing the relationship between variables they think influence purchases of their products.C. A negative relationship exists between two variables if low levels of one variable are associated with low levels of another.D. The strength of association is determined by the size of the correlation coefficient, with smaller coefficients indicating a stronger association.E. The null hypothesis for the Pearson correlation coefficient states that there is a strong association between two variables.
Answer: B
B. Marketers are often interested in describing the relationship between variables they think influence purchases of their products is true of relationships between variables.
A curvilinear relationship is more complex than a linear relationship as it involves the relationship between variables not being linear but described by a curve. Marketers, researchers, and analysts use different research methods to determine the relationship between different variables and how these variables affect the consumer’s behavior or outcome.
A negative relationship exists between two variables if high levels of one variable are associated with low levels of another. The Pearson correlation coefficient measures the strength and direction of a linear relationship between two continuous variables; the coefficient ranges from -1 to +1, and larger values indicate stronger associations between variables.
Therefore, option B is correct as marketers use statistical techniques to analyze the data collected on different variables that affect the purchase of their products. They use this information to make informed decisions regarding marketing strategies and product development. Understanding the relationship between variables is crucial in making effective decisions.
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