To accurately isolate cause and effect, experimenters should use
A) random assignment.
B) naturalistic observation.
C) case studies.
D) correlation coefficients.
The Correct Answer and Explanation is:
Correct Answer: A) Random assignment
Explanation
To accurately isolate cause and effect in psychological research or any scientific experiment, random assignment is essential. Random assignment means that participants are placed into different groups (typically experimental and control groups) purely by chance, rather than by choice or any characteristic. This technique ensures that any preexisting differences among individuals are equally distributed across groups, which helps eliminate confounding variables—factors other than the independent variable that might affect the outcome.
By using random assignment, researchers can confidently infer that changes in the dependent variable (the outcome being measured) are due to the manipulation of the independent variable (the factor being tested) and not due to other uncontrolled factors. This control allows for a true experiment, which is the only method that can establish a causal relationship.
Let’s compare this to the other choices:
- B) Naturalistic observation involves watching subjects in their natural environment without interference. While this can provide valuable descriptive data, it does not allow researchers to control variables or determine cause-and-effect relationships.
- C) Case studies involve in-depth analysis of a single individual or a small group. Though useful for generating hypotheses, they lack generalizability and control, making it difficult to establish causality.
- D) Correlation coefficients measure the strength and direction of the relationship between two variables. However, correlation does not imply causation. For example, just because ice cream sales correlate with drowning incidents doesn’t mean one causes the other; a third variable (hot weather) likely influences both.
In conclusion, random assignment is the only method among the options that allows researchers to control extraneous variables and establish clear cause-and-effect relationships, which is crucial for scientific validity and accurate experimental conclusions.
