Deck 8: Correlation

Question 1

A Pearson's correlation coefficient of -.5 would be represented by a scatterplot in which:

A)The regression line slopes upwards.
B)The data cloud looks like a circle and the regression line is flat.
C)There is a moderately good fit between the regression line and the individual data points on the scatterplot.
D)Half of the data points sit perfectly on the line.

Answer 1

C

Question 2

The table below contains scores from six people on two different scales that measure attitudes towards reality TV shows. $\begin{array} { | c | c | } \hline \begin{array} { c } \text { Attitudes towards Watching RealityTV } \\\text { Scale }\end{array} & \text { The General Reality TV Scale } \\\hline 3 & 2 \\\hline 7 & 5 \\\hline 4 & 3 \\\hline 1 & 1 \\\hline 8 & 7 \\\hline 6 & 7 \\\hline\end{array}$ Based on intuition rather than computation, which of the following is the value of the coefficient of determination between the two scales?

A).85
B)-.85
C).085
D)85

Answer 2

.85

Question 3

Imagine a researcher wanted to investigate whether there was a significant correlation between IQ and annual income, but she had reason to believe that work ethic would influence both of these variables. What should she do?

A)Conduct a partial correlation to look at the relationship between IQ and annual income while partialling out the effect of work ethic.
B)Conduct a semi-partial correlation to look at the relationship between IQ and annual income while partialling out the effect of work ethic.
C)Conduct a partial correlation to look at the relationship between work ethic and annual income partialling out the effect of IQ.
D)Conduct a semi-partial correlation to look at the relationship between IQ and work ethic while partialling out the effect of annual income.

Answer 3

A

Question 4

Which correlation coefficient would you use to look at the correlation between gender and time spent on the phone talking to your mother?

A)Kendall's correlation coefficient, τ
B)Pearson's correlation coefficient, r
C)The biserial correlation coefficient, r_b
D)The point-biserial correlation coefficient, r_pb

Question 5

If two variables are significantly correlated, r = .67, then:

A)The relationship is weak.
B)The variables are independent.
C)There is no unique variance.
D)They share variance.

Question 6

How much greater is the shared variance between two variables if the Pearson correlation coefficient between them is -.4 than if it is .2?

A)Half as much
B)Four times as great
C)Two times as great
D)A quarter as much

Question 7

The relationship between two variables partialling out the effect that a third variable has on one of those variables can be expressed using a:

A)Partial correlation
B)Point-biserial correlation
C)Semi-partial correlation
D)Bivariate correlation

Question 8

Which of the following statements about Pearson's correlation coefficient is not true?

A)It varies between -1 and +1.
B)It can be used as an effect size measure.
C)It can be used on ranked data.
D)It cannot be used with binary variables (those taking on a value of 0 or 1).

Question 9

The table below contains scores from six people on two different scales that measure attitudes towards reality TV shows. $\begin{array} { | c | c | } \hline \begin{array} { c } \text { Attitudes towards Watching RealityTV } \\\text { Scale }\end{array} & \text { The General Reality TV Scale } \\\hline 3 & 2 \\\hline 7 & 5 \\\hline 4 & 3 \\\hline 1 & 1 \\\hline 8 & 7 \\\hline 6 & 7 \\\hline\end{array}$ Based on intuition rather than computation, which of the following is the value of the correlation coefficient between the two scales?

A).1
B).92
C)9.0
D)-.92

Question 10

Looking at the table below, which variables were the most strongly correlated? $$\begin{array} { | l | l | l | l | l | } \hline & & { \text { Work ethic } } & \text { Annual income } & \text { IQ } \\\hline \text { Work ethic } & \begin{array} { l } \text { Pearson's } \\\text { correlation }\end{array} & 1.000 & .72 & .66 \\\hline & \text { Sig. (2-tail) } & . & .001 & .000 \\\hline & \text { N } & 550 & 550 & 550 \\\hline \text { Annual income } & \begin{array} { l } \text { Pearsor's } \\\text { correlation }\end{array} & .72 & 1.000 & .47 \\\hline & \text { Sig. (2-tail) } & .000 & . & .03 \\\hline & \text { N } & 550 & 550 & 550 \\\hline \text { IQ } & \begin{array} { l } \text { Pearson's } \\\text { correlation }\end{array} & .66 & .47 & 1.000 \\\hline & \text { Sig. (2-tail) } & .000 & .03 & . \\\hline & \text { N } & 550 & 550 & 550 \\\hline\end{array}$$

A)Work ethic and annual income
B)Work ethic and IQ
C)Annual income and IQ
D)None of the correlations are significant

Question 11

If a correlation coefficient has an associated probability value of .02 then:

A)The hypothesis has been proven.
B)There is only a 2% chance that we would get a correlation coefficient this big (or bigger) if the null hypothesis were true.
C)The results are important.
D)We should accept the null hypothesis.

Question 12

The correlation between two variables A and B is .12 with a significance of p < .01. What can we conclude?

A)That there is a small relationship between A and B.
B)That there is a substantial relationship between A and B.
C)All of these.
D)That variable A causes variable B.

Question 13

A scatterplot shows:

A)The average value of groups of data.
B)Scores on one variable plotted against scores on a second variable.
C)The frequency with which values appear in the data
D)The proportion of data falling into different categories.

Question 14

Which of the following could not be a correlation coefficient:

A)-.27
B)2.7
C)0
D).27

Question 15

If you have a curvilinear relationship, then:

A)It is not appropriate to use Pearson's correlation because it assumes a linear relationship between variables.
B)Pearson's correlation can be used in the same way as it is for linear relationships.
C)You can use Pearson's correlation; you just need to remember that a curve indicates that the variables are not linearly related.
D)Transforming the data won't help.

Question 16

What do the results in the table below show? $$\begin{array} { | l | l | l | l | } \hline & & { \text { Work produrtivity } } & { \begin{array} { c } \text { Time spent on } \\\text { Facebook }\end{array} } \\\hline \text { Work pradurtivity } & \text { Pearson's correlation } & 1.000 & - 94 \\\hline & \text { Sig. (2-tail) } & & .000 \\\hline & \text { N }&100&100\\\hline \begin{array} { l } \text { Time spent on } \\\text { Facebook }\end{array} & \text { Pearsan's correlation } & - 94 & 1.000 \\\hline & \text { Sig.(2-tail) } & .000 \\\hline & \text { N } & 100 & 100 \\\hline\end{array}$$

A)In a sample of 100 people, there was a strong negative relationship between work productivity and time spent on Facebook, r = -.94, p < .001.
B)In a sample of 100 people, there was a weak negative relationship between work productivity and time spent on Facebook, r = -.94, p < .001.
C)In a sample of 100 people, there was a non-significant negative relationship between work productivity and time spent on Facebook, r = -.94, p < .001.
D)In a sample of 100 people, there was a strong negative but non-significant relationship between work productivity and time spent on Facebook, r = -.94, p > .001.

Question 17

When interpreting a correlation coefficient, it is important to look at:

A)The magnitude of the correlation coefficient.
B)All of these.
C)The significance of the correlation coefficient.
D)The +/- sign of the correlation coefficient.

Question 18

A correlation of .5 would produce a scatterplot in which the slope:

A)Is downwards (from the bottom right corner to the top left corner of the graph).
B)Is flat (horizontal).
C)Is upwards (from the bottom left corner to the top right corner of the graph).
D)Is vertical.

Question 19

The table below contains scores from six people on two different scales that measure attitudes towards reality TV shows. $\begin{array} { | c | c | } \hline \begin{array} { c } \text { Attitudes towards Watching RealityTV } \\\text { Scale }\end{array} & \text { The General Reality TV Scale } \\\hline 3 & 2 \\\hline 7 & 5 \\\hline 4 & 3 \\\hline 1 & 1 \\\hline 8 & 7 \\\hline 6 & 7 \\\hline\end{array}$ Using the scores above, the two scales are likely to:

A)Correlate negatively.
B)Correlate positively.
C)Be uncorrelated.
D)Have identical means.