The most common correlation is the Pearson correlation that measures
The most common correlation is the Pearson correlation that measures the degree and the direction of the linear relationship between two variables; when there is a perfect linear relationship, every change in the X variable is accompanied by a corresponding change in the Y variable (Gravetter, 2021). So, a correlation is a statistical technique used to measure and describe the relationship between two variables. A positive correlation is a relationship in which two variables tend to change in the same direction and a negative correlation is a correlation in which two variables tend to go in opposite directions (Gravetter, 2021). The Pearson correlation consists of a ratio comparing the coverability of X and Y (the numerator) with the variability of X and Y separately (the denominator) (Gravetter, 2021). It’s important to address the fact that a correlation simply describes a relationship between two variables and It does not explain why the two variables are related so it cannot be interpreted as proof of a cause-and-effect relationship between the two variables (Gravetter, 2021).
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