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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
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
The particular projection which an investigator believes is most likely to give an accurate prediction of the future value of some process. Commonly used in the context of the anal
Case-cohort study : The research design in epidemiology which involves the sampling of controls at the outset of the study that is to be compared with the cases from the cohort. Th
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi
Bartlett decomposition : The expression for the random matrix A which has a Wishart distribution as the product of the triangular matrix and the transpose of it. Letting each of x
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo
Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric max
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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