Correlation analysis

Correlation analysis is a statistical technique used to measure the strength and direction of the relationship between two variables. It's often employed to determine if and how changes in one variable are associated with changes in another variable.
Positive Correlation: When two variables change in the same direction, they are said to be positively correlated. This means that as one variable increases, the other variable also tends to increase, and vice versa. A correlation coefficient close to +1 indicates a strong positive correlation.
Example: There is a positive correlation between the amount of studying a student does and their exam scores. As the amount of studying increases, exam scores tend to increase as well.

Negative Correlation: When two variables change in opposite directions, they are negatively correlated. This means that as one variable increases, the other variable tends to decrease, and vice versa. A correlation coefficient close to -1 indicates a strong negative correlation.
Example: There is a negative correlation between outdoor temperature and sales of winter coats. As the temperature increases, sales of winter coats tend to decrease.

Understanding the direction of correlation is important in interpreting the relationship between variables and making predictions based on that relationship.