Sdt also assumes that the stimuli generated by the noise condition vary
naturally for that hidden variable. As is often the case elsewhere, sdt, in
addition, assumes that the hidden variable values for the noise follow a normal
distribution. Recall at this point, that when a variable x follows a Gaussian
(a.k.a Normal) distribution, this distribution depends upon two parameters:
the mean (denoted µ) and the variance (denoted σ
2
). It is defined as: