Sentence examples for binomial distribution can detect from inspiring English sources

We demonstrate how the practical application of the binomial distribution can detect response bias in specific psychiatric disorders such as PTSD and can provide empirically grounded probabilistic evidence of malingering.

In terms of the concept of independence, the experiment leading to the binomial distribution can be described as follows.

The binomial distribution can be approximated as the Poisson distribution p n, nπ r s 2 / Ω.

When n is sufficiently large (e.g., n≥20), which is generally satisfied by the molecular communication systems, the binomial distribution can be approximated by a normal distribution [15,33].

The negative binomial distribution can be derived from a two-stage model for the distribution of a discrete variable Y (Venables and Ripley [2002]).

It is well known that for a large number of trials (i.e., when increases) the binomial distribution can be approximated by a normal distribution.

The negative binomial distribution can be seen as a mixture of Poisson distributions where the median values are drawn from a gamma distribution [17].

The Negative Binomial distribution can model the over-dispersed Poisson gene count where ϕ > 0 and reduces to the Poisson distribution as ϕ → 0.

The results proved that the beta-binomial distribution can be very useful for analyzing vegetation landscapes.

In a fixed-effects model, the beta-binomial distribution can be used when there is overdispersion with respect to the binomial distribution.

Two commonly used approaches which use the negative binomial distribution to detect differential expression are DESeq (Anders and Huber, 2010) and edgeR (Robinson et al., 2010).