Mkt 412 Chapter 12

While studying the relationship between advertising and sales growth, a researcher determines that the relationship is sometimes weak and at other times moderate. This variation from one situation to another is the variation in the _____ of the relationship between advertising and sales growth. A. strength of association B. presence C. type D. direction E. dispersion

A. strength of association

When the correlation coefficient is weak, the researcher must consider two possibilities: A. there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is not linear and must be investigated further. B. there is a consistent, systematic relationship between the two items in the population, but it is not linear and must be investigated further. C. there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and must be investigated further. D. there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and does not need to be investigated further. E. there is a consistent, systematic relationship between the two items in the population, but it is linear and must be investigated further.

A. there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is not linear and must be investigated further.

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.

B. Marketers are often interested in describing the relationship between variables they think influence purchases of their products.

Which of the following is the recommended statistic when two variables have been measured using ordinal scales? A. Goodman and Kruskal's lambda B. Spearman rank order correlation coefficient C. Pearson correlation coefficient D. Non-parametric hypothesis coefficient E. Goodman and Kruskal's gamma

B. Spearman rank order correlation coefficient

In a certain town, when the ownership of automobiles went up, the number of service stations also went up. This illustrates the concept of: A. codependence. B. co-alteration. C. covariation. D. coexistence. E. convergence

C. covariation.

Which of the following statements is true of the correlation analysis? A. The null hypothesis for the Pearson correlation coefficient states that there is always a strong association between two variables. B. The Pearson correlation coefficient measures the degree of linear association which ranges from 0 to 1.0. C. The larger the correlation coefficient, the weaker the association between two variables. D. The null hypothesis for the Pearson correlation coefficient states that the correlation coefficient is zero. E. The Pearson correlation coefficient measures the degree of linear association between three variables.

D. The null hypothesis for the Pearson correlation coefficient states that the correlation coefficient is zero.

In calculating the Pearson correlation coefficient, we assume that: A. when the correlation coefficient is weak, there is a consistent, systematic relationship between the two variables. B. the relationship we are trying to measure is curvilinear. C. the variables we want to analyze have a binomially distributed population. D. the variables have been measured using interval- or ratio-scaled measures. E. when the correlation coefficient is strong and significant, the two variables are associated in a curvilinear fashion.

D. the variables have been measured using interval- or ratio-scaled measures.

If a consistent and systematic relationship is not present between two variables: A. a strong association is evident. B. there is a moderate relationship. C. an insubstantial relationship exists. D. there is no relationship. E. there is a weak association.

D. there is no relationship.

A researcher plots a scatter diagram of two variables. The dots on the plot are scattered roughly as a circle. This indicates that the relationship (covariation) between the two variables is: A. linear, positive. B. linear, negative. C. circular, positive. D. circular, negative. E. very close to zero.

E. very close to zero.

A positive relationship between X and Y means that increases in X are associated with decreases in Y.

False

If the correlation coefficient is between 0.0 and 0.2, then there is a good chance the null hypothesis will be rejected.

False

The coefficient of determination is calculated by taking the square root of the correlation coefficient.

False

When two variables have a curvilinear relationship, the formula that best describes the linkage is very simple.

False

A scatter plot wherein the dots form an ellipse can be described as a positive relationship.

True

Covariation refers to the degree of association between two variables.

True

Independent variables are also called predictor variables.

True

It is possible for a correlation to be statistically significant and still lack substantive significance.

True

Scatter diagrams are a visual way to describe the relationship between two variables and the covariation they share.

True

The strength of association is determined by the size of the correlation coefficient.

True

To measure whether a relationship exists, we rely on the concept of statistical significance.

True

Use of the Pearson correlation coefficient assumes the variables have a normally distributed population.

True