BMD3024 Lecture 04 (Part 1)

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

• t varies between –1 and +1.

• It can be used as an effect size measure.

• It can be used on ranked data.

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

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

• The magnitude of the correlation coefficient.

• The significance of the correlation coefficient.

• The +/– sign of the correlation coefficient.

• All of these.

The correlation between two variables A and B is 0.12 with a significance of p < .01. What can we conclude?

• That there is a small relationship between A and B.

• That there is a substantial relationship between A and B.

• That variable A causes variable B.

• All of these.

15. 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.

. Which of the following could not be a correlation coefficient:

• –.27

• 2.7

• 0

• .27