The basic concept is to create homogeneous blocks in which the nuisance factors are held constant and the factor of interest is allowed to vary. When we can control nuisance factors, an important technique known as blocking can be used to reduce or eliminate the contribution to experimental error contributed by nuisance factors. Blocking used for nuisance factors that can be controlled The method was successfully applied in the theory of sums of dependent random variables and in Extreme Value Theory. The blocks method helps proving limit theorems in the case of dependent random variables. In Probability Theory the blocks method consists of splitting a sample into blocks (groups) separated by smaller subblocks so that the blocks can be considered almost independent. An example of a blocking factor might be the sex of a patient by blocking on sex, this source of variability is controlled for, thus leading to greater accuracy. Typically, a blocking factor is a source of variability that is not of primary interest to the experimenter. 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. Such a design is called a "randomized complete block design." This design will be more sensitive than the first, because each person is acting as his/her own control and thus the control group is more closely matched to the treatment group block design This is a workable experimental design, but purely from the point of view of statistical accuracy (ignoring any other factors), a better design would be to give each person one regular sole and one new sole, randomly assigning the two types to the left and right shoe of each volunteer. Both groups are then asked to use their shoes for a period of time, and then measure the degree of wear of the soles.
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This type of experiment is a completely randomized design. Given a group of n volunteers, one possible design would be to give n/2 of them shoes with the new soles and n/2 of them shoes with the ordinary soles, randomizing the assignment of the two kinds of soles. Intervention: Suppose a process is invented that intends to make the soles of shoes last longer, and a plan is formed to conduct a field trial.In this instance the researcher is blocking the elevation factor which may account for variability in the pesticide's application. A treatment group (the new pesticide) and a placebo group are applied to both the high elevation and low elevation areas of grass. The grass area contains a major elevation change and thus consists of two distinct regions - 'high elevation' and 'low elevation'.
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Elevation: An experiment is designed to test the effects of a new pesticide on a specific patch of grass.This reduces sources of variability and thus leads to greater precision. The sex of the patient is a blocking factor accounting for treatment variability between males and females.
![p value minitab express p value minitab express](https://i.ytimg.com/vi/_S6CZ0KxkmY/maxresdefault.jpg)
There are two levels of the treatment, drug, and placebo, administered to male and female patients in a double blind trial.