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Bootstrap: The data-based simulation method/technique for the statistical inference which can be used to study the variability of the estimated characteristics of the probability distribution of a set of observations and give con?dence intervals for the parameters in situations where these are difficult or impossible to derive in the usual manner. (The use of term bootstrap derives from the phrase 'to pull oneself up by the one's bootstraps'.) The general idea and approach of the procedure involves sampling with the replacement to produce random samples of size n from the original data, x1; x2; ... ; xn; each of these is called as a bootstrap sample and each gives an approximate idea of the parameter of interest. Repeating the process the large number of times provides the desired information on the variability of the estimator and the approximate 95% con?dence interval can, for instance, be derived from the 2.5% and 97.5% quantiles of the replicate values.
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
The risk of being able to recognize the respondent's confidential information in the data set. Number of approaches has been proposed to measure the disclosure risk some of which c
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Intercropping experiments are the experiments including growing two or more crops at same time on the same patch of land. The crops are not required to be planted nor harvested at
Personal probabilities : A radically special approach for allocating probabilities to events than, for instance, the commonly used long-term relative frequency approach. In this ty
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
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Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
Bivariate boxplot : A bivariate analogue of boxplot in which the inner area contains 50%of the data, and a 'fence' helps to identify the potential outliers. Robust methods or techn
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
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