# User:Garrett E. McMath/Notebook/Junior Lab/2008/11/24/Summary

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^{SJK 17:29, 17 December 2008 (EST)}## Summary

We first had assumed given what we knew about the expirement that the product of the dwell time and the number of passes should be all that matters. As is shown in the data and the analysis in Excell this was not the case. As is shown in the Excel sheet our percent error had a rough linear trend that went down with more passes and up with longer dwell times. I put four different trendlines on each graph; linear, logarithmic, power, and exponential, given that none of the R squared values were very high I concluded that it could not be done quite that simply. I believe that there is a perfect dwell time to get the best data and it appears to be in the 1 ms range, this hypothesis is strengthened by the lab manual which mentions this time to be used. Given that I created a third graph using only the ms time range data sets. It again has a very rough linear trend showing that the more passes done in the ms time range will give smaller margin of error which is given by the fact that a poisson distribution should have equal mean and variance. I have not been able to determine why the data is so bad as far as showing a clear linear trend. We did however on the last day set up the expirement to run in the ms time range for approx. 7 days worth of passes so we will see if this much larger data set will prove the hypothesis more definitively.

Trial | Dwell | Passes | Mean | Variance | Deviation (%) |
---|---|---|---|---|---|

1 | ? | ? | 4.085938 | 4.431801 | 8.46474 |

2 | ? | ? | .292969 | .239323 | 18.31111 |

3 | ? | ? | 1.113281 | 1.355744 | 21.77915 |

4 | 10ms | 120 | 4.40234375 | 5.01787684 | 13.9819406 |

5 | 400ms | 1 | 1.421875 | 0.966422 | 32.03189 |

6 | 8ms | 300 | 8.769531 | 8.374127 | 4.508843 |

7 | 200ms | 20 | 13.0625 | 8.552941 | 34.52294 |

8 | 100ms | 20 | 6.746094 | 5.798024 | 14.05361 |

9 | 1s | 1 | 3.460938 | 1.637684 | 52.68092 |

10 | 400us | 1800 | 2.625 | 3.223529 | 22.80112 |

11 | 1ms | 600 | 2.226563 | 2.113174 | 5.092535 |

12 | 1ms | 1200 | 4.519531 | 4.383931 | 3.000322 |

13 | 1ms | 2400 | 9.023438 | 8.407292 | 6.828283 |

14 | 1ms | 4800 | 18.20313 | 18.49975 | 1.629555 |

15 | 200ms | 3 | 2.332031 | 1.791284 | 23.18783 |