4.8.1 Correlation

Correlation refers to the statistical relationship between two or more variables.

It measures the degree to which two variables are related to each other, and the direction and strength of that relationship.

It can be one of the three types.

Negative correlation refers to a statistical relationship between two variables in which an increase in the value of one variable is associated with a decrease in the value of the other variable.
In other words, as one variable goes up, the other tends to go down.
An example of positive correlation could be the relationship between the number of hours a person works and their income. As the number of hours worked increases, the person’s income tends to increase as well, which suggests a positive correlation between these two variables.

Positive correlation refers to a statistical relationship between two variables in which an increase in the value of one variable is associated with an increase in the value of the other variable.
In other words, as one variable goes up, the other tends to go up as well.
An example of negative correlation could be the relationship between the amount of time a person spends watching television and their academic performance. As the amount of time a person spends watching television increases, their academic performance tends to decrease, which suggests a negative correlation between these two variables.

No correlation refers to a statistical relationship between two variables in which there is no consistent pattern of relationship between the two.
In other words, changes in one variable are not associated with changes in the other variable.
An example of no correlation could be the relationship between the size of a person’s feet and their favorite color. In general, changes in a person’s foot size are not associated with changes in their favorite color, and vice versa. This lack of correlation suggests that there is no meaningful relationship between these two variables.