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Question: 1 / 875

In regression analysis, what is the role of the correlation coefficient?

To show the time taken for a project to complete

To represent the average of a data set

To determine the degree of correlation between variables

The correlation coefficient is a statistical measure that evaluates the strength and direction of the relationship between two variables. It quantifies how closely related the changes in one variable correspond to changes in another variable. A correlation coefficient close to +1 indicates a strong positive correlation, meaning as one variable increases, the other also tends to increase. Conversely, a coefficient close to -1 signifies a strong negative correlation, indicating that as one variable increases, the other tends to decrease. A value around 0 suggests little to no linear relationship between the variables. By focusing specifically on the degree of correlation, the correlation coefficient serves as a crucial tool in regression analysis for researchers and analysts seeking to understand relationships between datasets and make predictions based on these relationships.

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To calculate the total cost of a project

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