Randomisere

Randomisere means to introduce randomness, typically by using a random mechanism to determine assignments, selections, or orders. In statistics and experimental research, randomisering reduces bias by ensuring that units such as participants, samples, or treatments are not allocated systematically to confounders. The term covers two main practices: random sampling from a population and random assignment of experimental units to groups or conditions.

In experimental design, randomisering assigns participants to groups (for example, treatment and control) using a random process, such as a random number generator or coin toss. Common methods include simple randomization, stratified randomization (to balance key characteristics across groups), block randomization, and minimization. Allocation concealment and blinding often accompany randomization to prevent selection and performance biases.

Random sampling and randomization are distinct. Random sampling aims to obtain a representative subset of a population for inference, while randomization aims to create equivalent groups within an experiment, enabling causal conclusions about treatment effects.

Historically, randomization is central to modern experimental design in agriculture, medicine, and social science. Analyses may use the randomization distribution; permutation tests rely on the actual randomization to compute p-values without strict parametric assumptions.

Applications of randomisere include clinical trials, psychology and education experiments, agriculture, and A/B testing in software. Practical considerations include reproducibility via seeds, and ethical issues when human participants are involved.