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Regression dilution is the term which is applied when a covariate in the model cannot be measured directly and instead of that a related observed value must be used in analysis. In common, if the model is correctly specified in the terms of the 'true' covariate, then an equivalent form of the model with a easy error structure will not hold for observed values. In such type of cases, ignoring the measured values will lead to the biased estimates of the parameters in the model. It is often also referred to as the errors in variables problem.
Difference b/w historigram and histogram
Conjugate prior : The distribution for samples from the particular probability distribution such that the posterior distribution at each stage of the sampling is of the identical f
The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.
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Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
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
Meta-analysis is the collection of techniques whereby the results of two or more independent studies are statistically combined to yield the overall answer to a question of intere
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