Since I've been doing some related work anyway, I might as well throw this in here. If anyone really, really, really needs to compute p or z values for whatever reason, Inquisit syntax for the standard normal CDF and its inverse is provided below. The code is based on Aludaat & Alodat (2008). More accurate algorithms are available, but I prefer these approximations because they're (a) relatively concise and (b) accurate enough for most purposes in psychology and related fields. Warning to unsuspecting readers: If you don't understand what this code does, chances are you don't need it.
# Normal CDF and Inverse Normal CDF functions
# This code is based on the approximations given in Aludaat & Alodat (2008).
# Results should be accurate to about two decimal places, with larger deviations
# for extreme values. This code is provided without any warranty.
# expressions.p_z computes p given z
# expressions.z_p computes z given p
/ p_z = if(values.z>0) 0.5*(1+sqrt((1-exp(-sqrt(m_pi/8)*pow(values.z,2))))) else
/ z_p = if(expressions.p_z>0.5) sqrt(-ln(1-pow(2*expressions.p_z-1,2))/sqrt(m_pi/8)) else
/ z = 0.6
/ items = ("z = <%values.z%> | p_z = <%expressions.p_z%> | z_p = <%expressions.z_p%>")
/ stimulusframes = [1=mytext]
/ validresponse = (anyresponse)