Location | Time x (min) | Distance y (m) |
---|---|---|

Dolihner | 0.0 | 0000 |

Pohnpei campus | 9.0 | 1250 |

Mesenieng outbound | 16.7 | 2600 |

Mesenieng inbound | 26.6 | 4200 |

Pwunso botanic | 35.7 | 5300 |

Dolihner | 41.9 | 6190 |

The table contains data from a run on Wednesday evening the sixth of February. While running, the runner juggled three tennis balls. This activity is called joggling.

- ______________ Does the relationship between distance and time appear to be linear, non-linear, or random?
- ______________ Determine the slope of the linear regression (best fit line) for the data.
- ______________ Determine the y-intercept of the linear regression for the data.
- ______________ Determine the correlation coefficient r.
- ______________ Is the correlation positive or negative?
- ______________ Is the correlation none, weak, moderate, strong, or perfect?
- ______________ Use the slope and intercept above to calculate the predicted distance covered by the runner after 25 minutes.
- ______________ A typical fun run on Pohnpei is 5000 meters. Use the slope and intercept to solve for the predicted time for the runner to run 5000 meters.
- ______________ Use the slope and intercept above to calculate the predicted distance covered by the runner after 250 minutes.
- ______________ Statistically speaking, can we safely predict the distance covered for 250 minutes of running and juggling?
- Why can we or why can we not safely predict the distance covered for 250 minutes of running and juggling?

Upcoming spring 2008 events, usually starting at 7:00 A.M. from Palm Terrace parking lot. Registration open at 6:30 A.M.

- PNI Rotary Club 5k Fun Run: March 01
- FSM National Fitness 5k Walk/Run: April 12 (maybe earlier)
- Women in Sport 5k: April 25
- COM-FSM 5k: May 03
- STAP 5k: May 24

Linear Regression Functions | |||
---|---|---|---|

Statistic or Parameter | Math symbol | Stat symbol | OpenOffice |

Slope | m | b | =slope(y-data;x-data) |

Intercept | b | a | =intercept(y-data;x-data) |

Correlation | r | =correl(y-data;x-data) | |

Coefficient of Determination | r^{2} |
=(correl(y-data;x-data))^2 |