Question 1

As the degree of linear relationship between two measures increases,
A)the absolute value of the correlation coefficient approaches 1.00.
B)the scatterplot resembles a straight line.
C)our ability to predict for these variables increases.
D)all of these

Accepted Answer

As the degree of linear relationship between two measures increases, the absolute value of the correlation coefficient approaches 1.00 (choice A), meaning that the relationship between the variables becomes stronger and more linear. This is reflected in the scatterplot which begins to resemble a straight line (choice B). With a stronger linear relationship, our ability to predict for these variables increases (choice C). Therefore, all of the choices are correct.

Question 2

A researcher finds a correlation of +.90 between two variables.Assuming the correlation coefficient was calculated correctly,which of the following is definitely not true?
A)As values on one measure increase,values on the other measure decrease.
B)Ability to make predictions for these variables is good.
C)A third variable may be present that explains the correlation.
D)The variables may be causally relateD.

Accepted Answer

A correlation coefficient of +.90 indicates a strong positive relationship between the two variables, meaning that as values on one measure increase, values on the other measure also tend to increase. Therefore, option A is definitely not true. Options B, C, and D are all possible and do not contradict the correlation coefficient of +.90.

Question 3

When two variables are correlated,our ability to make ___________ increases.
A)causal inferences for these variables
B)predictions for these variables
C)predictions about a third variable
D)causal inferences about a third variable

Accepted Answer

Correlation allows us to make predictions about one variable based on the other. However, correlation does not imply causation, so we cannot make causal inferences without further research or experiments. We also cannot make predictions about a third variable unless we have additional information or evidence to support it.

Question 4

Which of the following is certainly not positively correlated?
A)SAT scores and college grades
B)number of errors and number correct on an exam
C)smoking and lung disease
D)high school grades and college grades

Accepted Answer

Number of errors and number correct on an exam are inversely correlated, meaning as one variable increases, the other variable decreases. In other words, if someone gets more answers correct on an exam, they will likely have fewer errors.

Question 5

Which of the following indicates the strongest correlation?
A)+.80
B)+.40
C)-.60
D)-.90

Accepted Answer

The correlation coefficient ranges from -1 to +1. A value of -1 indicates a perfect negative correlation, 0 indicates no correlation, and +1 indicates a perfect positive correlation. Therefore, a correlation coefficient of -0.90 indicates a very strong negative correlation, which is the strongest correlation among the given choices.

Question 6

A correlation coefficient ranges from
A)0.0 to +1.00
B)0.0 to -1.00
C)-1.00 to 0.0
D)-1.00 to +1.00

Accepted Answer

The correlation coefficient measures the strength and direction of the relationship between two variables, and it can range from -1.00 (perfect negative correlation) to +1.00 (perfect positive correlation). A value of 0.0 indicates no correlation between the variables. Therefore, the correct answer is D, which includes both positive and negative values ranging from -1.00 to +1.00.

Question 7

A negative correlation indicates that as values for one measure ___________,the values for the other measure ____________.
A)decrease,remain constant
B)increase,remain constant
C)increase,increase
D)increase,decrease

Accepted Answer

A negative correlation means that as one variable increases, the other variable decreases. Therefore, Option D is the best answer. Options A and B state that one variable remains constant, which is not indicative of a negative correlation. Option C states that both variables increase, which is indicative of a positive correlation.

Question 8

One reason we may not make causal conclusions based only on correlational evidence is that a correlation between two variables
A)may be zero.
B)may be negative.
C)does not tell us about the possible direction of causality.
D)never involves causally related variables.

Accepted Answer

Correlation does not determine the direction of causality. There may be a third variable that causes both variables to have a correlation or the causal direction may be the opposite of what we assume. Therefore, we should not draw any causal conclusions solely based on correlational evidence. Options A, B and D are not adequate for this question.

Question 9

The direction (positive or negative)of a correlation is indicated by
A)the absolute value of the correlation.
B)numbers between 0.0 and 1.00.
C)the sign of the coefficient.
D)our ability to make predictions for the variables.

Accepted Answer

The sign of the coefficient (either positive or negative) indicates the direction of the correlation. A positive coefficient indicates a positive correlation, whereas a negative coefficient indicates a negative correlation. The absolute value of the correlation coefficient indicates the strength or magnitude of the correlation, but not its direction. Numbers between 0.0 and 1.00 are used to represent the strength of the correlation. Our ability to make predictions for the variables depends on the strength and direction of the correlation, as well as other factors such as sample size and the presence of confounding variables.

Question 10

A correlation coefficient is a ________ summary of the degree of relationship between two sets of scores.
A)subjective
B)qualitative
C)quantitative
D)graphical

Accepted Answer

A correlation coefficient is a statistical measure that quantifies the degree to which two variables are related. As such, it provides a quantitative summary of the relationship between two sets of scores. The other options (subjective, qualitative, and graphical) do not accurately describe what a correlation coefficient is.

Question 11

It was suggested in the textbook that the correlation between measures of intelligence and mental illness is close to
A)0.00
B)-.50
C)+.50
D)+1.00

Accepted Answer

The correlation between intelligence and mental illness is generally considered to be close to 0.00, indicating little to no direct relationship.

Question 12

One important reason for displaying correlational data in a scatterplot prior to computing a correlation coefficient is to determine whether
A)the means for the two variables are the same.
B)the relationship between the variables is nonlinear.
C)the x- and y-axis for each variable has appropriate endpoints.
D)the causal variable is graphed on the x-axis.

Accepted Answer

A scatterplot allows us to visually inspect the relationship between two variables and determine if the relationship is linear or nonlinear. This is important because the correlation coefficient only measures linear relationships between variables, so if the relationship is nonlinear, the correlation coefficient may not accurately represent the strength or direction of the relationship. Therefore, it is important to display correlational data in a scatterplot prior to computing a correlation coefficient to ensure that the relationship between the variables is appropriately represented. The other options listed (A, C, and D) are not directly related to determining the appropriateness of a scatterplot for computing a correlation coefficient.

Question 13

The relationship between a correlation coefficient and a confidence interval for the population correlation Þ"rho")is
A)the same as between a sample mean and a population mean.
B)such that the correlation coefficient provides an estimate of rho.
C)such that the more sampling error there is for the correlation coefficient,the wider the confidence interval for rho.
D)all of these

Accepted Answer

The answer of The relationship between a correlation coefficient and...

Quiz 11: Data Analysis and Interpretation: Part I Describing Data,confi Dence Intervals, Correlation

As the degree of linear relationship between two measures increases,

A researcher finds a correlation of +.90 between two variables.Assuming the correlation coefficient was calculated correctly,which of the following is definitely not true?

When two variables are correlated,our ability to make ___________ increases.

Which of the following is certainly not positively correlated?

Which of the following indicates the strongest correlation?

A correlation coefficient ranges from

A negative correlation indicates that as values for one measure _,the values for the other measure __.

One reason we may not make causal conclusions based only on correlational evidence is that a correlation between two variables

The direction (positive or negative) of a correlation is indicated by

A correlation coefficient is a ________ summary of the degree of relationship between two sets of scores.

It was suggested in the textbook that the correlation between measures of intelligence and mental illness is close to

One important reason for displaying correlational data in a scatterplot prior to computing a correlation coefficient is to determine whether

The relationship between a correlation coefficient and a confidence interval for the population correlation Þ"rho") is