Data table

Location | Distance (km) | Speed (kph) |
---|---|---|

Forest loop lap | 3.6 | 8.3 |

Spanish wall OAB | 4.1 | 11.0 |

Lower Town Loop Right | 4.8 | 8.8 |

Airport OAB | 7.9 | 8.8 |

Nett Bridge → Spanish Wall | 8.9 | 8.4 |

Airport OAB + Dainy | 9.7 | 9.0 |

PICS loop + Airport OAB | 10.1 | 9.7 |

PICS via KasEl Koahn | 10.2 | 8.9 |

Palipowe → Spanish Wall | 11.6 | 8.7 |

Second bridge in U OAB | 13.3 | 8.8 |

Badger state trail, Monroe, Wisconsin | 14.2 | 8.6 |

Yellowstone State Park, Wisconsin | 14.4 | 8.7 |

County C, LaFayette County, Wisconsin | 16.6 | 9.1 |

INS Half Marathon Pohnpei | 19.7 | 9.5 |

I noted in one section that a distance runner runs at a fixed speed, and that I tend to run the same speed regardless of whether the distance is long or short. The data table contains a sample of runs including the location and route of a run, the distance in kilometers, and my speed in kilometers per hour.

- ______________ Determine the slope of the linear trend line for the data.
- ______________ Determine the y-intercept of the linear trend line for the data.
- ______________ Use the slope and intercept to calculate the predicted speed for a distance of 18 km.
- ______________ Use the slope and intercept to predict the distance for a speed of 9 kph.
- ______________ Determine the correlation r.
- ______________ What is the strength of relationship?
- ______________ Determine the coefficient of determination.
- ______________ Based on the strength of the correlation, is the linear trend line able to accurately model the relationship between the distance I run and the speed at which I run?
- ______________ Does the analysis you did above provide
*support***or***contradict*my statement that I tend to run at the same speed regardless of the distance?