# Physics307L F07:People/Trujillo/Poisson

## POISSON

**Definition**

The Poisson Distribution is a discrete distribution which takes on the values X = 0, 1, 2, 3, ... . It is often used as a model for the number of events (such as the number of telephone calls at a business or the number of accidents at an intersection) in a specific time period. It is also useful in ecological studies, e.g., to model the number of prairie dogs found in a square mile of prairie.

The Poisson distribution is determined by one parameter, lambda. The distribution function for the Poisson distribution is :

Where is the amount of successes in a given period and is the amount of ocurances.

**Data**

We took data using a Multichannel Analyzer (MCA)which detects the amount of events occurring in a particular time period. Each channel represents the number of bins in time. The RAW data is found here

^{SJK 00:17, 10 December 2007 (CST)}Dwell Time | Average | |
---|---|---|

80ms | .45714 | 0.70703 |

100ms | .4683 | 0.62891 |

200ms | .9374 | 1.2070 |

400ms | 2.585 | 2.7617 |

800ms | 5.745 | 6.0234 |

1s | 7.7272 | 7.3242 |

10s | 73.902 | 73.366 |

**Summary**

Well, at first i was thinking that this experiment was going to be easy but it turns out that the majority of the lab is not taking the data but analyzing the data. I originally thought that I would have time to cook up snazzy LabVIEW program that would display all the distributions it an animated mode and a "single shot" mode but. I got some insight from Tomas on house exactly this is supposed to work being that he went above and beyond on the analysis.