Приклади вживання A normal distribution Англійська мовою та їх переклад на Українською
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For example, you can use a normal distribution to characterize the population of individuals' heights,
say, a normal distribution as the prior for his speed,
allowing the loudspeaker system to receive clean program material containing a normal distribution of energy levels.
often applies to slightly non-symmetric distributions that resemble a normal distribution, but it is not always true and in general the
None means the Expected estimate is used as is. Low risk means that a normal distribution is used.
and applies this to a normal distribution(as a two-tailed test), thus yielding the rule of two standard deviations(on a normal distribution) for statistical significance.
This suggests Bitcoin price movements are smooth, like a normal distribution, rather than characterized by fat tails,
identically distributed according to a normal distribution and that the boundary condition that the derivative of the log likelihood with respect to the true variance is zero,
Suppose a population has a normal distribution.
What is a normal distribution of data?
But we're going to have a normal distribution.
We also assume that the noise has a normal distribution.
The hazard function for a normal distribution is a monotonically increasing.
Quantitative traits often have a'normal' distribution in the population.
One of the most common assumptions is that the population data have a"normal distribution.".
the distribution of human skills generally follows a normal distribution that is symmetric about an average value.
the central limit theorem says that the distribution of the average will be closely approximated by a normal distribution.
One can standardize statistical errors(especially of a normal distribution) in a z-score(or"standard score"),
One can standardize statistical errors(especially of a normal distribution) in a z-score(or"standard score"),
While the distribution used for the approximation might be a normal distribution, this is not always so