r coding to account for residual variance what is the value of the x variable for r can regressions take y values? i want to avoid bias in my regression model. what is the sigma model what is the difference between a mean squared error and a back transform what would make a linear regression model biased what is the code for calculating the mean squared error in r if a variable is back transformed to square root, is this a valid method for the residuals? r what is back transform what is an example of back transformation with a linear model r is used to account for what? do you need to include mean squared error what is the back transformation in r what is the value of y in a sigma what model is used to account for residual variance what is the code to calculate the residual variance in r how to do a back transform in r what is the correct method of back transform how to account for mean squared error in r if r back transforms the variable to the square root, does it have a bias?