In regression, predictors with small coefficients of variation that are almost constant can cause numerical problems. For example, the variable YEAR with values from 1970 to 1975 has a small coefficient of variation and numerical differences between the variables are contained in the fourth digit. The problem is compounded if YEAR is squared. You could subtract a constant from the data, replacing YEAR with YEARS SINCE 1970, which has values 0 to 5.

If the coefficient of variation is moderately small, some loss of statistical accuracy will occur. In this case, Minitab alerts you that the predictor is almost constant. If the coefficient of variation is very small, Minitab eliminates the predictor from the model, and displays a message.

You can use the TOLERANCE subcommand with the REGRESS session command to force Minitab to keep a predictor in the model that has a small coefficient of variation. However, lowering the tolerance can be dangerous, possibly producing numerically inaccurate results.