Interpreting regression results

Interpreting regression output. I haven’t seen better explanation.



It was the nightmare of last week. Stata said “multi collinearity between variables” I tried with excluding one variable and than another and the problem was solved at last. We determined the highly collinear variables with “correlation matrix”

After that variables that has p>t which are bigger than 0,1 became problem. I combined some variables and excluded some again. We are continuing. (I must add something for interpreting frontier and regression results)

Anyway, wanted to share “what is collinearity” From Read more of this post

Linear Regression  is a very good web site for simple explanations. “Predicting” dependent variables with independent variables. Predict is important word here.


The word regression was used by Frances Galton in 1985. It is defined as “The dependence of one variable upon other variable”. For example, a weight depends upon the heights. The yield of wheat depends upon the amount of fertilizer. In regression we can estimate the unknown values of one (dependent) variable from known values of the other (independent) variable. Read more of this post