What does the strength of association in tests of relationships indicate?

The strength of association in tests of relationships primarily indicates the predictability of one variable from another. This means that the relationship between the two variables allows researchers to make assertions about how one variable can influence or predict outcomes in another variable. A strong association implies that knowing the value of one variable gives a good indication of the value of the other variable, which is crucial for understanding causal relationships in research.

For instance, if there is a strong correlation between exercise frequency and body weight, we can reasonably predict that as exercise frequency increases, body weight might decrease. This predictive capability is essential in fields like medicine, psychology, and social sciences as it helps inform interventions and improve outcomes.

The other options do not capture the complete visualization of relationships as effectively as the concept of predictability does. The total number of observations is more about the size of the data set than the strength of association. The extent of change in a variable refers to how much one variable changes without necessarily indicating a consistent predictive relationship. The correlation between outcomes describes a measure of the relationship but does not inherently convey the predictability aspect that is central to understanding the strength of association.