LINEAR CALIBRATION GRAPH AND ITS CONFIDENCE BANDS FROM REGRESSION ON TRANSFORMED DATA.

David A. Kurtz, James L. Rosenberger, Gwen J. Tamayo

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Scopus citations

Abstract

Linear calibration graphs were constructed from chromatographic response values by means of least squares statistical regression techniques to calculate amount estimates. The amount inverval estimates reflect both the uncertainties of measuring the response values and the uncertainty of the calibration graph. The following steps were followed: transformation of response variables to constant variance across the graph using a family of power transformations approach, transformation of the amount variable with similar transformations towards linearity, calculation of the regression coefficients by sums of squares, and solving the regression equation for unknowns.

Original languageEnglish (US)
Title of host publicationACS Symposium Series
PublisherACS
Pages133-165
Number of pages33
ISBN (Print)0841209251
StatePublished - Jan 1 1985

Publication series

NameACS Symposium Series
ISSN (Print)0097-6156

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)

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    Kurtz, D. A., Rosenberger, J. L., & Tamayo, G. J. (1985). LINEAR CALIBRATION GRAPH AND ITS CONFIDENCE BANDS FROM REGRESSION ON TRANSFORMED DATA. In ACS Symposium Series (pp. 133-165). (ACS Symposium Series). ACS.