Skewness measures lack of symmetry in a distribution arising from one side of the distribution having a longer tail than the other.
At the far left-hand side of the distribution are the bottom 5percentt of the IQ distribution, the Very Dull, with IQs under 75.
Confidence intervals (CIs) were based on distributions of these two parameters for 10 000 of these replicates, and observed values were considered significant if they fell within the tails of these distributions (defined as the extreme 250 values on each side of the distribution, i.e., P < 0.05).
The logistic distribution is considered inappropriate for modeling lifetime data because left hand side of its distribution extends to negative infinity, and this could conceivably result in modeling negative times-to-failure.
As can be seen in the figure, most of the treatment households are found to the right of the distribution, while most of the control households are found in the left side of the distribution.
Positive skewness indicates that the tail on the right side of the distribution is longer or fatter than that of the left side, and the mass of the distribution is concentrated on the left of the figure.
Statistical analysis of ChIP-based [ 9, 11- 19] 19] has showed that the left part of the empirical distribution is reach with the noise resulted from relatively low avidity BE and the right side of the distribution is represented by relatively high-avidity TF- DNA binding.
In Fig. 6 it is obvious that only in the left side of the distribution, of the 11 TEs "favored" on the ES, the gap is more then a third of the distribution.
The nNUF = 0.25 value, at the right side of the distribution curve, was used in further analyses of tumour detection in individual patients.
