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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.
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
The equation linking the height and weight of the children between the ages of 5 and 13 and given as follows here w is the mean weight in kilograms and h the mean height in
Briefly explain the importance of forecasting for managers?
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
Kalman filter : A recursive procedure which gives an estimate of the signal when only the 'noisy signal' can be observed. The estimate is efficiently constructed by putting the exp
Probability weighting is the procedure of attaching weights equal to inverse of the probability of being selected, to each respondent's record in the sample survey. These weights
Recursive models are the statistical models in which the causality flows in one direction, that is models which include only unidirectional effects. Such type of models do not inc
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
The procedure for clustering variables in the multivariate data, which forms the clusters by performing one or other of the below written three operations: * combining two varia
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