Which statement best describes randomization in experimental design?

Which statement best describes randomization in experimental design?

• A. It centralizes bias.
• B. It ensures identical subjects.
• C. It randomly assigns groups to control variables.
• D. It measures p-values.

Answer: (C)

Randomization creates comparable groups by chance, so differences in outcomes can be attributed to the intervention rather than preexisting differences. The best description is that subjects are allocated to treatment and control groups randomly, which helps balance variables that could influence the result, including factors you can’t measure. This balancing of control variables reduces confounding and supports valid statistical inference about the effect of the treatment. Randomization does not centralize bias; it works to minimize it. It also doesn’t make subjects identical, since you can’t make individuals perfectly the same. And p-values come from the data analysis after the study, not from the randomization process itself.

Randomization creates comparable groups by chance, so differences in outcomes can be attributed to the intervention rather than preexisting differences. The best description is that subjects are allocated to treatment and control groups randomly, which helps balance variables that could influence the result, including factors you can’t measure. This balancing of control variables reduces confounding and supports valid statistical inference about the effect of the treatment. Randomization does not centralize bias; it works to minimize it. It also doesn’t make subjects identical, since you can’t make individuals perfectly the same. And p-values come from the data analysis after the study, not from the randomization process itself.