What does internal validity assess in an experiment?

What does internal validity assess in an experiment?

• A. The accuracy of participant feedback
• B. The influence of external factors on the results
• C. The degree to which results are attributed to the independent variable
• D. The overall length of the study

Answer: (C)

Internal validity assesses the degree to which the results of an experiment can be attributed to the independent variable rather than other factors. It is concerned with the integrity of the experimental design, ensuring that any changes in the dependent variable can be confidently linked to manipulations of the independent variable. A high level of internal validity means that researchers can be more certain that the outcomes observed are a direct consequence of the experimental treatment and not influenced by confounding variables or biases. In practice, this involves controlling for various threats to internal validity, such as selection biases, maturation effects, or history effects, which could otherwise provide alternative explanations for the results. A strong internal validity allows researchers to draw conclusions with greater confidence regarding cause-and-effect relationships within the study.

Internal validity assesses the degree to which the results of an experiment can be attributed to the independent variable rather than other factors. It is concerned with the integrity of the experimental design, ensuring that any changes in the dependent variable can be confidently linked to manipulations of the independent variable. A high level of internal validity means that researchers can be more certain that the outcomes observed are a direct consequence of the experimental treatment and not influenced by confounding variables or biases.

In practice, this involves controlling for various threats to internal validity, such as selection biases, maturation effects, or history effects, which could otherwise provide alternative explanations for the results. A strong internal validity allows researchers to draw conclusions with greater confidence regarding cause-and-effect relationships within the study.