### Abstract

Language | English |
---|---|

Pages | 36-37 |

Number of pages | 2 |

Volume | 2009 |

Specialist publication | Microbiologist |

Publication status | Published - Jun 2009 |

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### Keywords

- prediction problem
- regression line

### Cite this

*Microbiologist*,

*2009*, 36-37.

}

*Microbiologist*, vol. 2009, pp. 36-37.

**Statnote 17: using a regression line for prediction and calibration.** / Hilton, Anthony; Armstrong, Richard A.

Research output: Contribution to specialist publication › Article

TY - GEN

T1 - Statnote 17: using a regression line for prediction and calibration

AU - Hilton, Anthony

AU - Armstrong, Richard A.

PY - 2009/6

Y1 - 2009/6

N2 - Two types of prediction problem can be solved using a regression line viz., prediction of the ‘population’ regression line at the point ‘x’ and prediction of an ‘individual’ new member of the population ‘y1’ for which ‘x1’ has been measured. The second problem is probably the most commonly encountered and the most relevant to calibration studies. A regression line is likely to be most useful for calibration if the range of values of the X variable is large, if there is a good representation of the ‘x,y’ values across the range of X, and if several estimates of ‘y’ are made at each ‘x’. It is poor statistical practice to use a regression line for calibration or prediction beyond the limits of the data.

AB - Two types of prediction problem can be solved using a regression line viz., prediction of the ‘population’ regression line at the point ‘x’ and prediction of an ‘individual’ new member of the population ‘y1’ for which ‘x1’ has been measured. The second problem is probably the most commonly encountered and the most relevant to calibration studies. A regression line is likely to be most useful for calibration if the range of values of the X variable is large, if there is a good representation of the ‘x,y’ values across the range of X, and if several estimates of ‘y’ are made at each ‘x’. It is poor statistical practice to use a regression line for calibration or prediction beyond the limits of the data.

KW - prediction problem

KW - regression line

UR - http://issuu.com/societyforappliedmicrobiology/docs/june09_micro

M3 - Article

VL - 2009

SP - 36

EP - 37

JO - Microbiologist

T2 - Microbiologist

JF - Microbiologist

SN - 1479-2699

ER -