Final answer:
Correlation is the association between variables where a change in one corresponds with a change in the other. The correlation coefficient quantifies this relationship, but it's crucial to note that correlation does not equate to causation.
Step-by-step explanation:
The term you are looking for is correlation. Correlation describes the association between variables in which a change in one variable is associated with a change in the other. For example, if we are studying the relationship between hours studied and test scores, we might find that as the number of hours studied increases, so do the test scores, indicating a positive correlation.
However, it's important to remember that correlation does not imply causation. Just because two variables change in relation to each other does not mean that one variable's change is causing the change in the other. A third variable, known as a confounding variable, could be influencing both. An often-cited example is the relationship between ice cream sales and drowning rates, which are correlated due to the confounding variable of warmer temperatures in summer months, rather than one causing the other.
The strength and direction of the correlation are quantified by the correlation coefficient, represented by the letter r. A value of +1 indicates perfect positive correlation, whereas a value of -1 indicates perfect negative correlation. A value of 0 means that there is no correlation. Graphical representation of data can also help in visualizing the relationship between two properties.