Linear vs Bayesian regression anomalies
I have been dipping my toes into Bayesian statistics and have seen some strange anomalies between the normal and Bayesian regression coefficients (see attached file). This is a very simple regression to predict kicking distance with right leg strength- both methods show that the model is good but the coefficients are in an order of magnitude different.
Linear regression intercept = 57.1 Bayesian intercept = 486.1 (same as the mean of the outcome variable!)
Linear regression R_strength = 6.425 Bayesian = 5.497
Using these in a simple linear prediction equation y = b0 + b1*x the normal coefficients are fine but are way out using the Bayesian coefficients.
Am I interpreting this incorrectly?