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A simple (not necessarily orthogonal) contrast is the difference between two means. A more complex contrast can test differences among several means (ex. with four means, assigning coefficients of –3, –1, +1, and +3), or test the difference between a single mean and the combined mean of several groups (e.g., if you have four means assign ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.
An example of a Levey–Jennings chart with upper and lower limits of one and two times the standard deviation. A Levey–Jennings chart is a graph that quality control data is plotted on to give a visual indication whether a laboratory test is working well.
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
The difference between the height of each man in the sample and the unobservable population mean is a statistical error, whereas; The difference between the height of each man in the sample and the observable sample mean is a residual.
The term 'Empirical Modelling' (EM) has been adopted for this work since about 1995 to reflect the experiential basis of the modelling process in observation and experiment. Special purpose software supporting the central concepts of observable, dependency and agency has been under continuous development (mainly led by research students) since ...
A contrast effect is the enhancement or diminishment, relative to normal, of perception, cognition or related performance as a result of successive (immediately previous) or simultaneous exposure to a stimulus of lesser or greater value in the same dimension. (Here, normal perception, cognition or performance is that which would be obtained in ...
Replication in statistics evaluates the consistency of experiment results across different trials to ensure external validity, while repetition measures precision and internal consistency within the same or similar experiments. [5] Replicates Example: Testing a new drug's effect on blood pressure in separate groups on different days.