The scale-invariant way to analyze two-dimensional experimental and theoretical data with statistical errors in both the independent and dependent variables is revisited by using what we call the triangular linear regression method. This is compared to the standard least-squares fit approach by applying it to typical simple sets of example data from the actual chemical literature. A new add-in for Microsoft Excel, LinEstXY, and ready-to-use formulas for the scale-invariant method are provided.