# 16.7: Critical Values for Grubb's Test

- Page ID
- 220804

The following table provides critical values for \(G(\alpha, n)\), where \(\alpha\) is the probability of incorrectly rejecting the suspected outlier and *n *is the number of samples in the data set. There are several versions of Grubb’s Test, each of which calculates a value for *G*_{ij}* *where *i *is the number of suspected outliers on one end of the data set and *j *is the number of suspected outliers on the opposite end of the data set. The critical values for *G *given here are for a single outlier, *G*_{10}, where

\[G_\text{exp} = G_{10} = \frac {|X_{out} - \overline{X}|} {s} \nonumber\]

The suspected outlier is rejected if *G*_{exp} is greater than \(G(\alpha, n)\).

\(\frac {\alpha \ce{->}} {n \ce{ v }}\) | 0.05 |
0.01 |

3 |
1.155 | 1.155 |

4 |
1.481 | 1.496 |

5 |
1.715 | 1.764 |

6 |
1.887 | 1.973 |

7 |
2.202 | 2.139 |

8 |
2.126 | 2.274 |

9 |
2.215 | 2.387 |

10 |
2.290 | 2.482 |

11 |
2.355 | 2.564 |

12 |
2.412 | 2.636 |

13 |
2.462 | 2.699 |

14 |
2.507 | 2.755 |

15 |
2.549 | 2.755 |