## The coefficient of determination:

• Question 4

The coefficient of determination:

Answers: a. Is the square root of the variance. b. Indicates whether the correlation coefficient is significant. c. Is the square root of the correlation coefficient. d. Is a measure of the amount of variability in one variable that is shared by the other.

• Question 6

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

Answers: a. Is vertical. b. Is upwards (from the bottom left corner to the top right corner of the graph). c. Is downwards (from the bottom right corner to the top left corner of the graph). d. Is flat (horizontal).

• Question 7

What do the results in the table below show?

u05q1 Question 18 table Work productivity Time spent of Facebook Work productivity Pearson’s correlation 1.000 -.94 Sig (2-tail) . .000 N 100 100 Time spent of Facebook Pearson’s correlation -.94 1.000 Sig. (2-tail) .000 . N 100 100

Answers: 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 strong negative but nonsignificant relationship between work productivity and time spent on Facebook, r = -.94, p > .001. d. In a sample of 100 people, there was a nonsignificant negative relationship between work productivity and time spent on Facebook, r = -.94, p < .001.

• Question 8

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

Answers: a. Half of the data points sit perfectly on the line. b. The regression line slopes upwards. c. There is a moderately good fit between the regression line and the individual data points on the scatterplot. d. The data cloud looks like a circle and the regression line is flat.

Question; 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 conclusion can be drawn from this finding? 1. Amount of time spent at work accounted for 71% of the variance in energy levels. 2. Spending more time at work caused participants to have less energy 3. There was a strong negative relationship between the number of hours spent at work and the energy levels. 4. The estimate of the correlation will be imprecise.

Question 7 If two variables are significantly related, r=.67, then:

1. They share a variance 2. The relationship is weak 3. There is no unique variance 4. The variables are independent