Приклади вживання Frequentist Англійська мовою та їх переклад на Українською
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Particularly when the frequency interpretation of probability is mistakenly assumed to be the only possible basis for frequentist inference.
By the end of the 19th century the frequentist interpretation was well established and perhaps dominant in the sciences.
these are of interest to statistical decision theory using the sampling distribution("frequentist statistics").
In classical(frequentist) statistics, the concept of marginal likelihood
coding theory(see e.g. minimum description length) or frequentist statistics(see frequentist matching).
so the frequentist approach rejects H 0{\displaystyle\textstyle H_{0}}
A frequentist 95% confidence interval means that with a large number of repeated samples,
In particular, frequentist developments of optimal inference(such as minimum-variance unbiased estimators,
Frequentist inference has been associated with the frequentist interpretation of probability,
it should have good frequentist properties.
so the frequentist approach rejects H 0{\displaystyle\textstyle H_{0}} as it disagrees with the observed data.
so the frequentist approach rejects H 0{\displaystyle\textstyle H_{0}}.
This is a frequentist approach, and it assumes that there are enough measurements to say something meaningful about β{\displaystyle{\boldsymbol{\beta}}}.
One interpretation of frequentist inference(or classical inference)
the differing results from the Bayesian and frequentist approaches can be explained as using them to answer fundamentally different questions, rather than actual disagreement between the two methods.
is considered significant in the frequentist approach, but its significance is overruled by the prior in the Bayesian approach.
such a probability need not have a frequentist or repeated sampling interpretation.
rather the probability of the evidence, given that the defendant is innocent(akin to a frequentist p-value).
the term'frequentist' was first used by M. G. Kendall in 1949,
By comparison, prediction in frequentist statistics often involves finding an optimum point estimate of the parameter(s)- e.g.,