1. The most widely used bivariate correlation coefficient is the

"rank-difference coefficient, rho."

"contingency coefficient, C."

"product-moment coefficient, r."

"correlation coefficient, eta."

2.If every increase in score on a test of literary knowledge is accompanied by an increase in score on an intelligence test, one can conclude that

there is a perfect negative relationship between literary knowledge and intelligence.

there is no relationship between literary knowledge and intelligence.

the correlation between the literary knowledge test and the intelligence test is 1.00.

intelligence causes literary knowledge.

3.If every point in a scattergram plotting variable X and variable Y falls on the line of best fit, we can conclude that

variable X predicts measured variable Y perfectly.

variable X explains none of the variance in variable Y.

the relationship between variables X and Y is positive.

Variable X causes variable Y or vice versa.

4.A correlation matrix is used to

show the extent to which each variable in a set of variables correlates with all the other variables in the set.

determine which predictor variables to enter into a multiple regression equation.

identify variables that have a restricted range.

all of the above

5.One disadvantage of correlational research is that

only two variables can be accommodated within a single correlational study.

the results of a correlational study do not permit strong conclusions about cause-and-effect relationships.

the variables in a correlational study cannot be measured reliably.

it is difficult to find published measures that satisfy the assumptions of a correlational research design.

6.An advantage of the correlational method is that

it can be used to analyze the relationships among many variables within a single study.

it indicates both the direction and the degree of the relationship between variables.

it can be used to predict academic achievement and other outcomes.

all of the above

7.The size of a research sample

determines the type of correlation coefficient that should be calculated.

affects the magnitude of an obtained correlation coefficient.

has no effect on the statistical significance of a correlation coefficient.

affects the statistical significance of a correlation coefficient.

8.A limitation of the shotgun approach to identify variables that correlate with a criterion variable is that

Group of answer choices

it cannot detect whether the observed relationships are positive or negative.

it cannot detect the magnitude of the observed relationships.

only a few variables can be accommodated in the research design.

some of the many measured variables are likely to correlate with the criterion by chance.

9.An important reason for making a scattergram is that it

provides a test of the statistical significance of the obtained correlation coefficient.

provides a measure of the confidence limits for the obtained correlation coefficient.

is helpful for detecting nonlinear relationships.

estimates the amount of shrinkage in a correlation coefficient when cross-validated.