![]() ![]() Negative values of “r” are associated with negative relationships.Positive values of “r” are associated with positive relationships.It is a unitless measure so “r” would be the same value whether you measured the two variables in pounds and inches or in grams and centimeters.This statistic numerically describes how strong the straight-line or linear relationship is between the two variables and the direction, positive or negative. The linear correlation coefficient is also referred to as Pearson’s product moment correlation coefficient in honor of Karl Pearson, who originally developed it. The sample size is n.Īn alternate computation of the correlation coefficient is: Where x̄ and s x are the sample mean and sample standard deviation of the x’s, and ȳ and s y are the mean and standard deviation of the y’s. To quantify the strength and direction of the relationship between two variables, we use the linear correlation coefficient: ![]() Linear Correlation Coefficientīecause visual examinations are largely subjective, we need a more precise and objective measure to define the correlation between the two variables. For example, when studying plants, height typically increases as diameter increases.įigure 5. Positive relationships have points that incline upwards to the right. Linear relationships can be either positive or negative. This is the relationship that we will examine.
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