Search results
Results from the WOW.Com Content Network
A "sampling unit" (or unit of observation) is typically thought of as an object that has been sampled from a statistical population. This term is commonly used in opinion polling and survey sampling. For example, in an experiment on educational methods, methods may be applied to classrooms of students. This would make the classroom as the ...
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
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.
(where ! denotes factorial) possible run sequences (or ways to order the experimental trials). Because of the replication, the number of unique orderings is 90 (since 90 = 6!/(2!*2!*2!)). An example of an unrandomized design would be to always run 2 replications for the first level, then 2 for the second level, and finally 2 for the third level.
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.
Also confidence coefficient. A number indicating the probability that the confidence interval (range) captures the true population mean. For example, a confidence interval with a 95% confidence level has a 95% chance of capturing the population mean. Technically, this means that, if the experiment were repeated many times, 95% of the CIs computed at this level would contain the true population ...
If the factor levels are simply categories, the correspondence might be different; for example, it is natural to represent "control" and "experimental" conditions by coding "control" as 0 if using 0 and 1, and as 1 if using 1 and −1. [note 1] An example of the latter is given below. That example illustrates another use of the coding +1 and −1.
Inferential statistics cannot separate variability due to treatment from variability due to experimental units when there is only one measurement per unit. Temporal pseudoreplication (Figure 5c in Hurlbert 1984) occurs when experimental units differ enough in time that temporal effects among units are likely, and treatment effects are ...