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Units are often referred to as being either experimental units or sampling units: An "experimental unit" is typically thought of as one member of a set of objects that are initially equal, with each object then subjected to one of several experimental treatments. Put simply, it is the smallest entity to which a treatment is applied.
Blocking (right) Blocking is the non-random arrangement of experimental units into groups (blocks) consisting of units that are similar to one another. Blocking reduces known but irrelevant sources of variation between units and thus allows greater precision in the estimation of the source of variation under study.
In the statistical theory of the design of experiments, blocking is the arranging of experimental units in groups (blocks) that are similar to one another. Typically, a blocking factor is a source of variability that is not of primary interest to the experimenter. [3] [4] No blocking (left) vs blocking (right) experimental design
Effect (of a factor): How changing the settings of a factor changes the response. The effect of a single factor is also called a main effect. A treatment effect may be assumed to be the same for each experimental unit, by the assumption of treatment-unit additivity; more generally, the treatment effect may be the average effect.
In scientific research, an experimental system is the physical, technical and procedural basis for an experiment or series of experiments. Historian of science Hans-Jörg Rheinberger defines an experimental system as: "A basic unit of experimental activity combining local, technical, instrumental, institutional, social, and epistemic aspects."
In medicine and the social sciences, the prevalence of experimental research varies widely across disciplines. When used, however, experiments typically follow the form of the clinical trial, where experimental units (usually individual human beings) are randomly assigned to a treatment or control condition where one or more outcomes are ...
In the statistical theory of design of experiments, randomization involves randomly allocating the experimental units across the treatment groups.For example, if an experiment compares a new drug against a standard drug, then the patients should be allocated to either the new drug or to the standard drug control using randomization.
Designed experiments with full factorial design (left), response surface with second-degree polynomial (right) In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors.