Search results
Results from the WOW.Com Content Network
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
A simple unit is one which represents a single condition without any qualification. A composite unit is one which is formed by adding a qualification word or phrase to a simple unit. For example, labour-hours and passenger-kilometer. Unit of analysis and interpretation: units in terms of which statistical data are analyzed and interpreted.
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.
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.
The study of statistical methods that are enabled by using computational methods, at the interface of statistics and computer science. concomitants In a statistical study, any variables whose values are unaffected by experimental treatments, such as a unit’s age, gender, and cholesterol level before starting an experimental diet. [1]
Inferential statistics cannot separate variability due to treatment from variability due to experimental units when there is only one measurement per unit. Sacrificial pseudoreplication (Figure 5b in Hurlbert 1984) occurs when means within a treatment are used in an analysis, and these means are tested over the within unit variance.
Experimental data in science and engineering is data produced by a measurement, test method, experimental design or quasi-experimental design. In clinical research any data produced are the result of a clinical trial. Experimental data may be qualitative or quantitative, each being appropriate for different investigations.
The unit of observation should not be confused with the unit of analysis.A study may have a differing unit of observation and unit of analysis: for example, in community research, the research design may collect data at the individual level of observation but the level of analysis might be at the neighborhood level, drawing conclusions on neighborhood characteristics from data collected from ...