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The type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatments are received. The simplest such design includes two groups of the subjects, one of which receives each of the two treatments, A and B, in the order AB, while the other takes them in the reverse order. This is called as a two-by-two crossover design. While the treatment comparison is 'within-subject' rather than the 'between-subject', it is likely to need fewer subjects to achieve the given power. The study of such designs is not necessarily straight- forward because of the possibility of the carryover effects, that is left over effects of the treatment received on the first occasion which remain present into the second occasion. An attempt to minimize this problem is many times made by including the wash-out period between the two treatment occasions. Some of the authorities have suggested that this type of design should only be used if such carryover effects can be ruled out a priori. Crossover designs are only applicable to the chronic conditions for which short-term relief of the symptoms is the goal rather than a cure of it.
Linked micro map plot is a plot which provides the graphical overview and the details for spatially indexed statistical summaries. The plot shows the spatial patterns and statisti
Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows therefor
how to get the proportional allocation of the give stratified random sampling example
Monty Hall problem : A apparently counter-intuitive problem in the probability which gets its name from the TV game show, 'Let's Make a Deal' hosted by the Monty Hall. On show a pa
Common cause failures (CCF): Simultaneous failures of the number of components due to a same reason. A reason can be external to the components, or it can be the single failure wh
Bayesian network : It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network c
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.
PRINCIPLES OF MODELLING IN OR.
The variables appearing on the right-hand side of equations defining, for instance, multiple regressions or the logistic regression, and which seek to predict or 'explain' response
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