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:

    Truth is the kind of error without which a certain species of life could not live. The value for life is ultimately decisive.
    Friedrich Nietzsche (1844–1900)

    In philosophical inquiry, the human spirit, imitating the movement of the stars, must follow a curve which brings it back to its point of departure. To conclude is to close a circle.
    Charles Baudelaire (1821–1867)

    A distinction of property results from that very protection which a free Government gives to unequal faculties of acquiring it.
    James Madison (1751–1836)