V.9:12 (482-485) SIDEBAR: Explaining r by Jim Bianco, C.M.T.
Product Description
EXPLAINING r
Correlation analysis measures the degree of relationship between two variables. The correlation coefficient r is one popular statistical index for this purpose. The values for r range between +1 to -1; a +1 reading indicates that the two variables are perfectly correlated, while a -1 reading indicates a perfect inverse relationship. An r of 0 indicates that the two variables have no correlation. The correlation coefficient r measures the relationship between two variables that are believed to be linear. For instance, a straight line is used to describe the relationship if the two variables were plotted on a graph using an X and Y axis. Sometimes, two variables will have a relationship that is described by a line that curves. The use of the formula for r is restricted to relationships that are linear.
The correlation coefficient measures only the degree of association between two variables. It is important to remember that r is not a measure of cause and effect. A large positive r does not mean that if one variable is large, this causes the other variable to be large.
The formula for r is :
Correlation analysis measures the degree of relationship between two variables. The correlation coefficient r is one popular statistical index for this purpose. The values for r range between +1 to -1; a +1 reading indicates that the two variables are perfectly correlated, while a -1 reading indicates a perfect inverse relationship. An r of 0 indicates that the two variables have no correlation. The correlation coefficient r measures the relationship between two variables that are believed to be linear. For instance, a straight line is used to describe the relationship if the two variables were plotted on a graph using an X and Y axis. Sometimes, two variables will have a relationship that is described by a line that curves. The use of the formula for r is restricted to relationships that are linear.
The correlation coefficient measures only the degree of association between two variables. It is important to remember that r is not a measure of cause and effect. A large positive r does not mean that if one variable is large, this causes the other variable to be large.
The formula for r is :
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