randomize

Randomize is the act of applying randomness to a process, decision, or assignment, typically by using chance rather than deliberate choice. The term combines random with the suffix -ize and denotes making something unpredictable or dependent on chance. In statistics and experimental research, randomization is a method used to assign participants, treatments, or interventions by chance, with the aim of reducing bias and creating comparable groups.

In experimental design, randomization helps ensure that differences observed between groups are more likely due to the treatment rather than confounding factors. Common methods include simple randomization (each unit has an equal chance of assignment), block randomization (ensuring balanced numbers across groups within blocks), and stratified randomization (randomization conducted within predefined subgroups). Proper randomization supports the validity of causal inferences.

In computer science, randomization is used to shuffle data, generate simulation inputs, or produce random numbers. Pseudo-random number generators produce sequences that appear random but are deterministic from a seed; true randomness can come from physical processes. Algorithms such as the Fisher–Yates shuffle implement unbiased random permutation.

Randomization also plays a role in data analysis and statistics, where permutation tests and Monte Carlo methods rely on reshuffling or resampling data under the null hypothesis to assess significance.

Limitations include the need for careful implementation, sufficient sample size, and practical constraints. Randomization does not eliminate all bias and is not a substitute for good study design, measurement, or analysis.