Chapter 7- Correlation

1.

1 point

A scatterplot shows:

The proportion of data falling into different categories.

Scores on one variable plotted against scores on a second variable.

The average value of groups of data.

The frequency with which values appear in the data.

2.

1 point

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

It cannot be used with binary variables (those taking on a value of 0 or 1).

It can be used on ranked data.

It can be used as an effect size measure.

It varies between –1 and +1.

3.

1 point

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

The magnitude of the correlation coefficient.

The +/– sign of the correlation coefficient.

The significance of the correlation coefficient.

All of these.

4.

1 point

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

All of these.

That there is a small relationship between A and B.

That variable A causes variable B.

That there is a substantial relationship between A and B.

5.

1 point

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

Point-biserial correlation

Bivariate correlation

Semi-partial correlation

Partial correlation

6.

1 point

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?

Conduct a partial correlation to look at the relationship between IQ and annual income while partialling out the effect of work ethic.

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

Conduct a partial correlation to look at the relationship between work ethic and annual income partialling out the effect of IQ.

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

7.

1 point

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

Is upwards (from the bottom left corner to the top right corner of the graph).

Is vertical.

Is flat (horizontal).

Is downwards (from the bottom right corner to the top left corner of the graph).

8.

1 point

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

Two times as great

Half as much

A quarter as much

Four times as great

9.

1 point

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

Kendall's correlation coefficient, τ

Pearson's correlation coefficient, r

The point-biserial correlation coefficient, rpb

The biserial correlation coefficient, rb

10.

1 point

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

The regression line slopes upwards.

Half of the data points sit perfectly on the line.

There is a moderately good fit between the regression line and the individual data points on the scatterplot

The data cloud looks like a circle and the regression line is flat.

11.

1 point

If you have a curvilinear relationship, then:

It is not appropriate to use Pearson's correlation because it assumes a linear relationship between variables.

Transforming the data won't help.

You can use Pearson's correlation; you just need to remember that a curve indicates that the variables are not linearly related.

Pearson's correlation can be used in the same way as it is for linear relationships.

12.

1 point

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

The relationship is weak.

The variables are independent.

There is no unique variance.

They share variance.

13.

1 point

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

The results are important.

We should accept the null hypothesis.

The hypothesis has been proven.

There is only a 2% chance that we would get a correlation coefficient this big (or bigger) if the null hypothesis were true.

14.

1 point

Which of the following could not be a correlation coefficient:

–.27

0

2.7

.27

15.

1 point

The coefficient of determination:

Is the square root of the variance.

Is the square root of the correlation coefficient.

Is a measure of the amount of variability in one variable that is shared by the other.

Indicates whether the correlation coefficient is significant.

16.

1 point

A Pearson's correlation of –.71 was found between number of hours spent at work and energy levels in a sample of 300 participants. Which of the following conclusions can be drawn from this finding?

Spending more time at work caused participants to have less energy.

There was a strong negative relationship between the number of hours spent at work and energy levels.

Amount of time spent at work accounted for 71% of the variance in energy levels.

The estimate of the correlation will be imprecise.