True/False(See related pages)

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Out of 10 questions, you answered 9 correctly with a final grade of 90%

9 correct (90%)

1 incorrect (10%)

0 unanswered (0%)

Your Results:

The correct answer for each question is indicated by a .

1 CORRECT The major characteristic of correlational research is to seek out associations amongvariables.

A) TRUE

B) FALSE

Feedback: The major characteristic of correlational research is to seek out associations

among variables.

2 CORRECT The variable that is used to make the prediction is called the criterion variable.

A) TRUE

B) FALSE

Feedback: The variable that is used to make the prediction is called the predictor

variable.

3 CORRECT The variable about which the prediction is made is called the predictor variable.

A) TRUE

B) FALSE

Feedback: The variable about which the prediction is made is the criterion variable.

4 CORRECT Both scatterplots and regression lines are used in correlational studies to predict a score on acriterion variable.

A) TRUE

B) FALSE

Feedback: Both scatterplots and regression lines are used in correlational studies to

predict a score on a criterion variable.

5 CORRECT Threat of maturation is possible whenever all instruments are administered to each subjectat a specified location but the location is different for different subjects.

A) TRUE

B) FALSE

Feedback: Location threat is possible whenever all instruments are administered to each

subject at a specified location but the location is different for different subjects.

6 CORRECT Almost all correlational studies revolve around three types of questions: Is variable X relatedto variable Y? What is the relationship among a large number of variables and what

predictions can be made on them? How well does variable P predict variable C?

A) TRUE

B) FALSE

Feedback: Almost all correlational studies revolve around the following types of

questions: Is variable X related to variable Y? What is the relationship among a large

number of variables and what predictions can be made on them? How well does variable

P predict variable C?

7

INCORRECTThe coefficient of determination indicates the strength of the correlation between the

combination of the predictor variables and the criterion variable.

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A) TRUE

B) FALSE

Feedback: True, although the correlation coefficient is more commonly used to indicate

strength of relationship. The coefficient of determination indicates the percentage of the

variability among the criterion scores that can be attributed to differences in the scores

of the predictor variable.

8 CORRECT Multiple regression is a technique that enables researchers to determine a correlationbetween a criterion variable and the best combination of two or more predictor variables.

A) TRUE

B) FALSE

Feedback: Multiple regression is a technique that enables researchers to determine a

correlation between a criterion variable and the best combination of two or more

predictor variables.

9 CORRECT Structural modeling is appropriate only when correlational research is combined with anexperiment.

A) TRUE

B) FALSE

Feedback: Structural modeling is a way to explore potential causal relationships. The

primary correlational methods used for this modeling are multiple regression, path

analysis and discriminate function analysis. These methods cannot verify causality since

only an experiment can do that. They can, however, illuminate the relationships among

variables and determine whether the data are consistent with theoretical expectations.

10

CORRECTIf the variable "hours spent in study" is positively correlated with the variable "score on the

test," we can be certain that the score on the test can be perfectly predicted from the hours

spent in study.

A) TRUE

B) FALSE

Feedback: A positive correlation means that the scores of one variable tend to go up or

down in the same manner as scores on the other variable. Thus, if the hours spent in

study positively correlate with scores on a test, then we can expect that students who

study the most typically get the highest test scores. This does not necessarily mean that

the extra study causes higher scores. A correlation can only suggest cause and effect. In

this example it is possible that the students who get the highest scores would get the

high scores even if they did not study so much.

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