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Weighted least squares is the method of estimation in which the estimates arise from minimizing the weighted sum of squares of the differences between response variable and its predicted value in terms of the model of interest. It is often used when the variance of response variable is thought to change over range of values of the explanatory variable(s), in which case the weights are usually taken as the reciprocals of the variance.
when there is tie in sequencing then what we do
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
explain the graphical method of measure of central tendency
A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of succes
Confounding: A procedure observed in some factorial designs in which it is impossible to differentiate between some main effects or interactions, on the basis of the particular d
Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occur
Ha: If hyperlipidemia is believed to be a side effect of second-generation antipsychotics (SGAs), then Hispanic patients with SGAs treatment will have the higher frequency of devel
In the time series plot and scatter graphs there were many outliers that were clearly visible. These have been removed to identify if they were influential or had high leverage and
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