In real life no one will regress from a give equation and end up with one bad number. If one ended with a bad number and force it to fit, it will give nothing but false information.
Suppose that the number you obtained from experiment is x = 0,2,4,6,8 y=0,6,12,18,8 and you know that they are close enough as anticipated based on your hypothesis, then you should have a good feel for which equation to fit.
Suppose that you did your experiment with no clue about the outcome, and you got x = 0,2,4,6,8 y=0,6,12,18,8. Then you must first graph you scattered diagram. If the diagram tells you that it is close to a straight line, you use straight-line equation. To confirm the goodness of fit, you find the coefficient of correlation. If the coefficient of correlation is too poor, you can go to next degree curve. You go to fit the quadratic curve. If quadratic curve’s coefficient of correlation is still poor, you can to up the next degree, i.e. the Cubic curve. Segue; you can go up to the most exotic Logistic curve.