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Latin square is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment effect can be attained. The rows and columns of the square depict the levels of the two extraneous factors. The treatments are represented by the Roman letters arranged such that no letter appears more than once in each row and column. The below drawn is an example of a 4 × 4 Latin square
Cauchy distribution : The probability distribution, f (x), can be given as follows where α is the position of the parameter (median) and the beta β a scale parameter. Moments
Nested design is the design in which levels of one or more factors are subsampled within one or more other factors such that, for instance, each level of a factor B happens at onl
Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is
The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for
Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularl
Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizin
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
facts and statistics about daycare
Data theory is anxious with how observations are transformed into data which can be analyzed. Data are thus viewed as the theory laden in the sense that the observations can be giv
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
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