Consistency in parameter labels

PS: I would add a helper equation there along the lines of "In regression we are finding the line that best relates our dependent variable (Y) to the independent variable (X), so we will typically want to know both the slope (how much Y increases for each increment in X) and possibly the intercept as well (how much Y we have even when X is 0). This is traditionally expressed as Y = b*X + C

In the conventions of statisticians, the intercept is termed βo, the slope β1. In SEM, we also model the error (epsilon: ϵ) inherent in our measurement of x, giving us:

y = β0 + β 1 ∗ x + ϵ

In R you may be used to running this as

  data(myRegData)
  myModel = lm(y~x, data= myRegData); 
  anova(myModel)

Here we will implement this in OpenMx...