Calibration Curve - Error in Calibration Curve Results

Error in Calibration Curve Results

As expected, the concentration of the unknown will have some error which can be calculated from the formula below. This formula assumes that a linear relationship is observed for all the standards. It is important to note that the error in the concentration will be minimal if the signal from the unknown lies in the middle of the signals of all the standards (the term goes to zero if )

s_x=\frac{s_y}{|m|}\sqrt{\frac{1}{n}+\frac{1}{k}+\frac{(y_{unk}-\bar{y})^2}{m^2\sum{(x_i-\bar{x})^2}}}

  • is the standard deviation in the residuals
  • is the slope of the line
  • is the y-intercept of the line
  • is the number standards
  • is the number of replicate unknowns
  • is the measurement of the unknown
  • is the average measurement of the standards
  • are the concentrations of the standards
  • is the average concentration of the standards

Read more about this topic:  Calibration Curve

Famous quotes containing the words error, curve and/or results:

    “Theoretically, I grant you, there is no possibility of error in necessary reasoning. But to speak thus “theoretically,” is to use language in a Pickwickian sense. In practice, and in fact, mathematics is not exempt from that liability to error that affects everything that man does.”
    —Charles Sanders Peirce (1839–1914)

    “And out again I curve and flow
    To join the brimming river,
    For men may come and men may go,
    But I go on forever.”
    —Alfred Tennyson (1809–1892)

    “It is perhaps the principal admirableness of the Gothic schools of architecture, that they receive the results of the labour of inferior minds; and out of fragments full of imperfection ... raise up a stately and unaccusable whole.”
    —John Ruskin (1819–1900)