Deck 9: Correlational Research Designs

Question 1

If the correlation between variables x and y is r = .50, then the effect size is

A) .25.
B) 0.
C) 1.00.
D) .50.

Answer 1

D

Question 2

R2 is to the multiple correlation coefficient as the coefficient of determination is to

A) the Pearson correlation coefficient.
B) the regression coefficient.
C) the multiple R.
D) the regression line.

Answer 2

A

Question 3

Which of the following is a table showing the correlations of many variables with each other?

A) A correlation matrix
B) A path analysis
C) A multiple regression analysis
D) A multiple scatterplot

Answer 3

A

Question 4

Which part of the correlation matrix is usually included in the research report?

A) The diagonal
B) The entire matrix
C) The upper triangle
D) The corners

Question 5

In a multiple regression analysis, the statistics that indicate the relationship between each of the predictor variables and the outcome variable are known as

A) Pearson correlations.
B) Chi squares.
C) coefficients of determination.
D) regression coefficients.

Question 6

Whereas a correlation matrix contains a series of Pearson correlation coefficients, a contingency table contains

A) validities.
B) frequencies.
C) regression lines.
D) samples.

Question 7

The technique of predicting a single outcome variable using a number of predictor variables is known as

A) meta-analysis.
B) causal modeling.
C) multiple regression.
D) inverse correlation.

Question 8

A contingency table is a table that

A) displays the number of individuals in each combination of two nominal variables.
B) shows the correlations of many variables with each other.
C) shows the relationships depicted in a scatterplot.
D) presents a chi-square statistic.

Question 9

A researcher found a positive correlation between income and job satisfaction in a sample of one hundred adults. The researcher should conclude

A) higher income causes job satisfaction.
B) job satisfaction causes higher income.
C) there is a third variable that causes both job satisfaction and income.
D) that any of the above may be correct, but he cannot tell which.

Question 10

Which of the following statistics are used to show the relationships between variables in a path analysis?

A) Regression coefficients
B) Pearson correlation coefficients
C) Multiple correlation coefficients
D) Chi-square statistics

Question 11

When the light level of a computer screen is moderate, task performance scores are high. When the light level of the computer screen is either very low or very high, task performance scores are low. The relationship between the light level and performance is

A) negative linear.
B) positive linear.
C) curvilinear.
D) independent.

Question 12

The Pearson product moment correlation coefficient is used to assess the association between

A) two quantitative variables.
B) two nominal variables.
C) one quantitative and one nominal variable.
D) two nominal variables and one quantitative variable.

Question 13

In a multiple regression analysis, which of the following are most similar to correlation coefficients?

A) The predictor variables
B) The outcome variables
C) The regression coefficients
D) The p-values

Question 14

Which of the following is a likely result of restriction of range?

A) The size of the correlation coefficient is reduced.
B) The causality between the predictor and outcome variable is reversed.
C) The size of the correlation coefficient is increased.
D) The direction of the correlation will be reversed.

Question 15

A linear relationship that moves from the top left corner of the scatterplot to the lower right corner of the scatterplot would be which of the following?

A) Independent
B) Curvilinear
C) Negative
D) Positive

Question 16

Which of the following statistics would be used to assess the relationship between two nominal variables?

A) The chi-square
B) The coefficient of determination
C) The correlation coefficient variable
D) The multiple correlation coefficient

Question 17

Which one of the following would NOT be found on the path diagram of a multiple regression analysis?

A) The predictor variables
B) The regression line
C) The outcome variable
D) The regression coefficients

Question 18

If the correlation between variables x and y is r = .50, then the coefficient of determination is

A) .25.
B) 0.
C) 1.00.
D) .50.

Question 19

Reciprocal causation occurs when

A) the causal relationship is exactly the opposite of what was hypothesized.
B) a third variable caused by the predictor variable causes the outcome variable.
C) the predictor variable causes the outcome variable and vice versa.
D) extraneous variables affect the relationship.

Question 20

Which of the following provides a visual image of the relationship between two quantitative variables?

A) A scatterplot
B) A correlation matrix
C) A contingency table
D) A schematic diagram

Question 21

Structural equation analysis is a technique that can be used to

A) compute multiple correlations matrices.
B) compare the chi-square value of two contingency tables.
C) enhance the correlation among two variables.
D) assess causal relationships using correlational data.

Question 22

Which of the following variables causes only the outcome variable, but not the predictor variable?

A) A common-causal variable
B) An extraneous variable
C) A mediating variable
D) A third variable

Question 23

Which of the following r values shows the strongest correlation between two variables?

A) r = .6
B) r = .3
C) r = 0
D) r = -.8

Question 24

Consider the following relationship between violent material and aggressive behavior: Violent TV arousal aggressive behavior. In this case, arousal can be described as a

A) predictor variable.
B) mediating variable.
C) common causal variable.
D) extraneous variable.

Question 25

A researcher finds that height and intelligence are correlated in children. The age of the child is probably which of the following?

A) A mediating variable
B) An extraneous variable
C) A common-causal variable
D) An outcome variable

Question 26

Jason finds a correlation of .85 between monthly homicide rates and monthly ice cream sales. However, he believes that the correlation is caused by monthly changes in temperature. In this case, temperature represents a(n) _____ variable.

A) outcome
B) predictor
C) spurious
D) extraneous

Question 27

Jarrod hypothesizes that getting plenty of sleep leads to lower blood pressure, and that lower blood pressure reduces stress. In this hypothesis, which of the following is the mediating variable?

A) Stress
B) Sleep
C) Blood pressure
D) The hypothesis does not have a mediating variable

Question 28

Which of the following is true about correlational research designs?

A) They provide no evidence about the causal relationships among the measured variables.
B) They are always analyzed using the Pearson correlation coefficient.
C) They are used when the variables are very difficult to measure.
D) The measurement of the outcome variable is likely to be invalid.

Question 29

In general, ______________ are more problematic than ________________ because they can produce spurious relationships.

A) extraneous variables; mediating variables
B) reciprocal variables; mediating variables
C) common-causal variables; extraneous variables
D) extraneous variables; common-causal variables

Question 30

A researcher is studying the relationship between a person's gender and his or her preference for three new premium television channels. Each participant is asked to choose the one channel that he or she prefers. The researcher will use which of the following statistical tests?

A) Chi square
B) ANOVA
C) t-test
D) p-value test

Question 31

In a correlational research design, a spurious relationship is caused by

A) an extraneous variable.
B) a common-causal variable.
C) an intervening variable.
D) a mediating variable.

Question 32

A research design in which the same individuals are measured more than once over a time period long enough that changes in the variables could occur is known as a

A) longitudinal design.
B) cross-sectional design.
C) path design.
D) beta design.

Question 33

A correlational study with two predictor variables and one outcome variable will be analyzed using which of the following statistics?

A) Chi square
B) ANOVA
C) Within participants correlation
D) Multiple regression

Question 34

In a correlational research design, Jonas finds that r = .82. Jonas's data demonstrates which of the following?

A) A nonlinear relationship
B) A negative linear relationship
C) A positive linear relationship
D) A curvilinear relationship

Question 35

A researcher finds that the number of times people carry an umbrella in a month is related to how fast the grass is growing This relationship is most likely to be

A) causal.
B) produced by an extraneous variable.
C) spurious.
D) produced by reciprocal causation.

Question 36

Which of the following analyses might be used to study the relationships in a longitudinal research design?

A) A panel analysis
B) A path analysis
C) A correlation matrix
D) A contingency table

Question 37

Which of the following represents the best interpretation of the beta weights in multiple regression?

A) The beta weights predict the value of each predictor variable.
B) The beta weights control for the effects of the other predictor variables.
C) The beta weights are equal to the correlation coefficients.
D) The beta weights do not need to be compared to a p-value.

Question 38

If we find that there is a positive correlation between variable x and variable y, which of the following is true?

A) X causes y.
B) Y causes x.
C) There are common-causal variables that cause both x and y.
D) Any of the above possibilities may be correct.

Question 39

A scientist hypothesizes that divorce can lead to depression and that depression can then lead to poor physical health. In this case, depression can be considered

A) a common-causal variable.
B) a mediating variable.
C) a third variable.
D) a path variable.

Question 40

Anita has collected a large correlation matrix in which each of several conceptual variables has been measured more than once. She wishes to assess both the reliability of her measurements and the correlations among the conceptual variables in one analysis. Which of the following statistical procedures is appropriate?

A) Structural Equation Analysis
B) Chi-square
C) Multiple regression
D) Coefficient alpha

Question 41

Wisneski, Lytle, and Skitka (2009) correlated measured religiosity and measured moral conviction with measured trust in authority. The researchers found that highly relious people showed _____ trust in authority whereas the highly moral people showed ____ trust in authoiry.

A) less; more
B) more; less
C) more variable; less variable
D) less variable; more variable

Question 42

In a study of the relationship between participant age and memory, the gender of the participant would represent a(n) _____ variable.

A) outcome
B) predictor
C) spurious
D) extraneous

Question 43

Wisneski, Lytle, and Skitka (2009) assessed the associations among measured religiosity, measured moral conviction, and measured trust in authority. The researchers used an analysis that controlled for the influence of each of the predictor variables on the outcome measure. Which of the following statistical analysis did they use?

A) ANOVA
B) Chi-Square
C) F Test
D) Multiple regression