Least square based parabolic regression to determine Calibration Constant in measurement

This paper highlights the use of Calibration Constant of Test & Measuring (T&M) equipment derived during calibration process, in measurement inference. The equipment user is much interested to find the true value of measurand against the measured quantity. In this paper, the Best-fit-curve is proposed to model a set of test results obtained during calibration by Least Square Error (LSE) based parabolic regression. Calibration Constant becomes more dominant rather than the detailed multi page test results to determine the actual value of measurement with certain degree of accuracy. This reduces interpolation error while calculating the true value other than testing points and also the measurement time. The Test setup is automated and the measured parameters are traceable to national standards.