The exogenous variables are the independent variables (x1, x2 ..) and the endogenous variables are the two latent variables. Maybe the g1 is our β1 because we want the covariance between the two latent variables?
I'm not so sure.
X = should be the variance and the variance is 1
1= is a regressions weight and it could be one of them: l1, l2, l3, l4, l5, l6
and the cov(X,Y) is the covariance between the two latent variables ?
Xi does not mean x1, x2 or x3. XI is the 14th letter of the Greek alphabet and in the picture above its the "ξ". In Addition to this in the model The residual variance of Eta(η) is chosen so that the total variance of Eta is 1. The l1, l2, l 3 and so on you can see the regression weights.
i don't know how to calculate the covariance between Xi and ETA(n) with the 6 factor loadings and gamma in the middle of the picture. The Variance of the latent variables is 1, so it is the fully standardised solution.. Furthermore i want to calculate the covariance between x2 and y2...