ABSTRACT
As we remember from Chapter 3, a quantitative trait (QT) is the trait that changes in continuous mode, where no discrete classes can be defi ned. However, we can measure such a trait and fi nd limits of its variation within a scale that is defi ned in a certain way. The QT’s distribution can be explained by the theory of Gauss, by the normal distribution, like this (Fig. 11.1.1):
F(x) = j (x; μσ2). (11.1)
Thus, the normal distribution is a distribution function of density of probability with two parameters; μ and σ2 are parameters of a function F(x), called mathematical expectation and variance; these parameters can be evaluated through the estimates of mean and standard deviation.
