What is the difference between positive correlation, negative correlation, and no correlation?
Answer
Positive Correlation:
Positive Correlation is when 2 variables move in the same direction. It shows a direct linear relationship, meaning an increase in one variable is directly associated with the increase of another variable. It works the same way with decreasing, if one variable is decreasing so is the other variable. On a scatterplot (which I have attached a screenshot of), positive correlation would be shown as a bunch of points clustered near an upward sloping line.
Some examples of positive correlation:
- The more someone exercises, the better their fitness is.
- As the temperature rises, ice cream sales tend to rise as well. Similarly, as the temperature falls, ice cream sales tend to fall as well.
- The more time you spend studying, typically reflects you making a higher grade.
Negative Correlation:
Negative Correlation is the opposite of positive correlation. As one variable decreases, the other variable increases and vice-versa. On a scatterplot, negative correlation is shown as a bunch of points clustered near a downward sloping line.
Some examples of negative correlation:
- The more time you watch TV, the less time you have available to study.
- As the temperature outside decreases, the more clothes you have to put on.
- The more you pay off a loan, the less debt you will be in.
No Correlation:
No correlation means their is no linear relationship. Each variable has no effect on the other variable. On a scatter plot, there will be not upward or downward sloping line, just a bunch of points scattered everywhere on the plot.
Some No Correlation Examples:
- Comparing people's height to their exam scores
- Comparing someone's shoe size to the amount of movies they watch.
- Comparing the amount of coffee one drinks to the length of their hair.
See how the variables have absolutely no relation to the other? That is no correlation.