The PEST algorithm is an adaptive staircase procedure that uses a subject's responses to derive a probability-based estimate based on a normal sigmoid-shaped psychophysical function to generate a different comparison interval on each successive trial.
Raw expression values were first normalized based on a normal distribution of genes with low expression levels as previously described [ 26, 27].
Response to lymphocyte transformation assay should be analyzed based on a normal range and using more than one stimulator.
Our data suggest that: 1) Analysis of lymphotoxin alpha response should be based on a normal range and analyzed using more than one stimulator; 2) The use of a cut-off value to classify patients with NCC as responders or non-responders to fungal antigens and mitogen is inadequate.
In this article, we limited our considerations to the normality assumption, because in frequentist statistics confidence intervals usually are based on a normal or t-distribution assumption.
The other approach is based on a normal approximation of a distribution associated with new mutations.
To get a better understanding of these framework guest interactions, a new theoretical procedure is proposed based on a normal mode analysis.
Particular emphasis is put on the optimal coefficients highlighted recently in a theoretical study based on a normal mode stability analysis.
We then generated 100 potential records by randomly adding or subtracting deviations based on a normal distribution from the running mean, with the standard deviation equal to that of the Hadley CRU data for 1986–2015 °C.1 °C).
According to 2015 data from the UN Food and Agriculture Organization, the average person in the US and Canada gets a full 90g a day, a fifth more than the recommended amount (based on a normal North American adult weight of about 80kg).
The distribution of X and Y positions were generated based on a normal distribution with σ = 0.15μm.
