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Assuming that the data is drawn from a Poisson distribution, one could use a likelihood ratio to compare the data from the group and knockout stages.
Assuming that the data is drawn from a Poisson distribution, one could use a likelihood ratio to compare the data from the group and knock-out stages.
It seems likely that many Americans would respond to these figures — and to the role poverty plays in poor health outcomes — by assuming that the data for all Americans is being skewed downward by the health of the poorest.
For instance, Zhang (2003) introduces a statistical test to find outliers by assuming that the data distribution is exponential.
Assuming that the data for smoothing is obtained by sampling some curve with noises, an expression for optimal curves is derived when the number of data becomes infinity.
We anticipate that the actual data covariance matrix will be diagonal, assuming that the data noise is caused by stationary and uncorrelated processes.
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Nevertheless, let's assume that the data on development gathered from local plans points to another coalition volte-face.
Most approaches assume that the data is outsourced to a single SP. Others assume that the data is outsourced to multiple, non-colluding SPs.
We assume that the data BW are the limited resource and could be dynamically changed [3].
We assume that the data contained in the headers are transmitted without error.
Assume that the data functions f, y d, p d, and the domain Ω are infinitely smooth.
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