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A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how to conduct the statistical aspects of an experiment and which action to take for each possible outcome. Choosing the decision function needs a loss function to be defined which assigns numerical values to making bad or good decisions. Explicitly a general loss function is denoted by L d; expressing how bad it would be to make decision d if the parameter value were. A quadratic loss function, it could be defined as and a bilinear loss function as
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
Item-total correlation is an extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
literature review of latin square design.
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
Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th
The growth in bad debt expense for Johnston office supply Company over this time period.If this rate continues,estimate the percentage increase in bad debts for 1997,relative to 19
Goodmanand kruskal measures of association is the measures of associations which are useful in the situation where two categorical variables cannot be supposed to be derived from
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
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