Table 1.

Degree . | r^{2} adjusted
. | Residual sum of squares . | d.f. . | F
. | P(F)
. | t for the highest term
. | P(t)
. |
---|---|---|---|---|---|---|---|

1 | 0.394 | 2240 | 14 | 10.75 | 0.0055 | -3.28 | 0.005 |

2 | 0.349 | 2232 | 13 | 5.03 | 0.0240 | 0.20 | 0.843 |

3 | 0.634 | 1159 | 12 | 9.67 | 0.0016 | 3.34 | 0.006 |

4 | 0.602 | 1155 | 11 | 6.68 | 0.0056 | -0.19 | 0.853 |

5 | 0.708 | 770 | 10 | 8.28 | 0.0025 | -2.23 | 0.050 |

Degree . | r^{2} adjusted
. | Residual sum of squares . | d.f. . | F
. | P(F)
. | t for the highest term
. | P(t)
. |
---|---|---|---|---|---|---|---|

1 | 0.394 | 2240 | 14 | 10.75 | 0.0055 | -3.28 | 0.005 |

2 | 0.349 | 2232 | 13 | 5.03 | 0.0240 | 0.20 | 0.843 |

3 | 0.634 | 1159 | 12 | 9.67 | 0.0016 | 3.34 | 0.006 |

4 | 0.602 | 1155 | 11 | 6.68 | 0.0056 | -0.19 | 0.853 |

5 | 0.708 | 770 | 10 | 8.28 | 0.0025 | -2.23 | 0.050 |

Total sum of squares 3959, d.f. 15.

The table includes the following: the degree of polynomial regression(Degree); the adjusted coefficient of determination (*r*^{2});the sum of squares about the regression (Residual sum of squares) and degrees of freedom (d.f.); the variance ratio (*F*) and the probability value, *P(F)*, testing the significance of the decrease in residual mean square; Student's *t*-test (*t* for the highest term) and its *P(t)* value for the introduction of the last term in the regression equation.

This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy.