Final answer:
Correlation research does not establish cause and effect, so one cannot infer that changes in one variable are causing changes in the other variable.
Step-by-step explanation:
Correlation research is useful in identifying relationships between variables, but it does not establish cause and effect. Just because a correlation exists between the healthiness of one's heart and the amount of fish oil in one's diet, it does not infer that changes in one variable are causing changes in the other variable.
Correlation does not indicate causation, and there could be other confounding variables that are influencing both variables of interest.
Using correlation design, a researcher found a relationship between the healthiness of one's heart and the amount of fish oil in one's diet. The researcher should conclude that although a relationship exists, one cannot infer that changes in one variable are causing changes in another variable.
Correlation does not indicate causation, which is a fundamental concept in research that highlights the limitations of correlational studies. While such studies are instrumental in identifying relationships between variables, they do not provide evidence of a causal relationship.
This misunderstanding can lead to the erroneous assumption that because two variables are correlated, one must be the cause of the other, which is not necessarily the case.