Correlation and their meaning
Correlation is a statistical measure that describes the relationship between two or more variables. It measures how changes in one variable are associated with changes in another variable.
Correlation can have different meanings based on its strength and direction:
1. Strength of correlation: This refers to how closely the variables are related to each other. It is measured on a scale from -1 to +1. A correlation value closer to -1 or +1 signifies a strong relationship, while values closer to 0 indicate a weak relationship.
2. Direction of correlation: It indicates the nature of the relationship between variables. There can be three types of correlations:
- Positive correlation: When the variables move in the same direction. For example, as the temperature increases, the ice cream sales also increase.
- Negative correlation: When the variables move in opposite directions. For example, as the price of a good increases, the demand for it decreases.
- No correlation: When there is no apparent relationship between the variables. Changes in one variable do not affect the other variable.
It is important to note that correlation does not imply causation. Just because two variables are correlated does not mean that one variable causes the changes in the other variable. Correlation only shows the association or relationship between variables, but not the cause-and-effect relationship.