Assessing the Strength of Linear Association with Correlation Coefficient

The video tutorial explains how to assess the strength of a linear association using the correlation coefficient. It covers the basics of scatterplots, types of correlation (positive, negative, and none), and how the correlation coefficient (r) is calculated and interpreted. Examples are provided to illustrate different levels of correlation, including perfect, strong, moderate, weak, and no correlation. The tutorial emphasizes that the correlation coefficient only measures linear relationships and provides guidelines for interpreting its value.

What does a positive correlation in a scatterplot indicate about the relationship between two variables?

• One variable increases as the other decreases.

• Both variables increase together.

• The variables are unrelated.

• There is no relationship between the variables.

What is the range of values for the correlation coefficient 'r'?

• -1 to 1

• -0.5 to 0.5

• 0 to 1

• 0 to 0.5

In a perfect positive linear correlation, what is the value of 'r'?

• -1

• 1

• 0.5

• 0

Which of the following represents a moderate positive correlation?

• r = 0.2

• r = 0.9

• r = 0.7

• r = -0.7

What does a correlation coefficient of 0 indicate?

• Perfect correlation

• No linear correlation

• Strong negative correlation

• Strong positive correlation

What is the correlation coefficient for a strong negative correlation?

• r = -0.9

• r = -0.5

• r = 0.9

• r = 0.5

If the correlation coefficient is negative, what does it imply about the relationship between the variables?

• There is no relationship.

• Both variables increase together.

• Both variables decrease together.

• One variable increases as the other decreases.