### 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 language | English (US) |
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Title of host publication | ACS Symposium Series |

Publisher | ACS |

Pages | 133-165 |

Number of pages | 33 |

ISBN (Print) | 0841209251 |

State | Published - Jan 1 1985 |

### Publication series

Name | ACS Symposium Series |
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ISSN (Print) | 0097-6156 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Chemistry(all)
- Chemical Engineering(all)

### Cite this

*ACS Symposium Series*(pp. 133-165). (ACS Symposium Series). ACS.

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*ACS Symposium Series.*ACS Symposium Series, ACS, pp. 133-165.

**LINEAR CALIBRATION GRAPH AND ITS CONFIDENCE BANDS FROM REGRESSION ON TRANSFORMED DATA.** / Kurtz, David A.; Rosenberger, James L.; Tamayo, Gwen J.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - LINEAR CALIBRATION GRAPH AND ITS CONFIDENCE BANDS FROM REGRESSION ON TRANSFORMED DATA.

AU - Kurtz, David A.

AU - Rosenberger, James L.

AU - Tamayo, Gwen J.

PY - 1985/1/1

Y1 - 1985/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0021975318&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0021975318&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0021975318

SN - 0841209251

T3 - ACS Symposium Series

SP - 133

EP - 165

BT - ACS Symposium Series

PB - ACS

ER -