Correlation Analysis

How can a correlation coefficient of +1 be interpreted?

• No relationship between the variables
• Perfect positive linear relationship
• Perfect negative linear relationship
• Weak positive linear relationship

How is covariance defined for a sample?

• It is divided by the standard deviation to obtain the correlation coefficient

• It measures the extent of variation in one variable associated with a variance in the other variable

• It measures the relationship between height and weight for individuals

• It is calculated using the differences of each observation from the mean

What does a correlation coefficient of 0 indicate?

• No linear relationship
• Weak positive correlation
• Perfect negative correlation
• Perfect positive correlation

What does the correlation coefficient measure?

• The correlation coefficient measures the strength and direction of the linear relationship between two variables.
• The correlation coefficient measures the ratio between two variables.
• The correlation coefficient measures the difference between two variables.
• The correlation coefficient measures the average of two variables.

Why does correlation not imply causation?

• There can be many reasons for statistical correlation between two variables

• It can only be used when there is a perfect positive linear relationship between variables

• It is only applicable when one variable causes another

• Causation can only be determined through regression analysis

What is the range of possible values for the correlation coefficient?

• 0 to 1
• -1 to 1
• 1 to 10
• -10 to 10

What is the purpose of regression analysis?

• The purpose of regression analysis is to predict future outcomes.
• To determine if the variation in one variable affects another variable

• The purpose of regression analysis is to determine causation between variables.
• The purpose of regression analysis is to measure the central tendency of a dataset.

What is the purpose of correlation analysis?

• The purpose of correlation analysis is to predict future outcomes.
• The purpose of correlation analysis is to compare two different populations.
• The purpose of correlation analysis is to determine the relationship between two variables.
• The purpose of correlation analysis is to determine causation between two variables.

What does a positive covariance value indicate?

• No relationship
• Inverse relationship
• Negative linear relationship
• Positive linear relationship

How can the interpretation of covariance be problematic?

• Covariance only measures linear relationships between variables.
• The larger the values of the variables, the larger the covariance, even if the relationship does not change

• Covariance cannot be used to compare the strength of relationships between different pairs of variables.
• Covariance is sensitive to the scale of measurement of the variables.