What type of hypothesis is typically used in correlation design?

• A. A hypothesis about group differences.
• B. A hypothesis about a causal relationship.
• C. A hypothesis about a relationship between two variables.
• D. A hypothesis that involves more than two variables.

Answer: (C)

In correlation design, the focus is on examining the relationship between two variables to determine whether they are associated with one another and the direction of that association. A hypothesis about a relationship between two variables is fundamental in this context because it enables researchers to predict how changes in one variable may relate to changes in another variable. For instance, a researcher might hypothesize that an increase in physical activity is associated with a decrease in levels of anxiety. This type of hypothesis does not imply causation; it simply indicates whether a relationship exists and helps identify patterns that can be further explored.

The other options do not align with the nature of correlation design. Hypotheses about group differences usually pertain to experimental designs where comparisons between distinct groups are made. Causal relationship hypotheses imply a cause-and-effect framework that correlational studies do not establish, as they cannot confirm whether one variable directly affects another. Lastly, while hypotheses involving more than two variables may arise in complex analyses, standard correlation design typically focuses on the simple association between two variables.