The major attribute of correlation analysis is the measurement of the association between two variables. It quantifies both the strength and direction of a linear relationship between variables without implying causation. This association is typically expressed by the correlation coefficient, which ranges from -1 to +1, where:
- +1 indicates a perfect positive linear relationship,
- -1 indicates a perfect negative linear relationship,
- 0 indicates no linear relationship.
Correlation analysis is fundamentally based on the assumption of linearity between the variables and is used to explore how closely two quantitative variables move together, whether positively or negatively
. In summary, the key attribute of correlation analysis is:
- Assessing the degree and direction of association between variables (positive, negative, or none),
- Quantifying this association with a correlation coefficient,
- Helping to identify relationships that might warrant further investigation, but not establishing causality
Thus, correlation analysis is primarily about detecting and measuring the association among variables.
