Lecture5 - ENU 4612C/5615C Nuclear Radiation Detection and...

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ENU 4612C/5615C Nuclear Radiation Detection and Instrumentation Lecture 5 Counting Statistics and Error Prediction (1)
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Counting Statistics and Error Prediction 1. Characterization of Data 2. Statistical Models 3. Applications of Statistical Models 4. Error Propagation
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Counting Statistics and Error Prediction 1. Characterization of Data
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1. Characterization of Data
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Example 1. Characterization of Data
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1. Characterization of Data
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1. Characterization of Data
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1. Characterization of Data = = = N i i e i i d x x d 1 0 : Residual x x i i = ε : Deviation
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1. Characterization of Data = = N i i x x N s 1 2 2 ) ( 1 = = N i e i x x N s 1 2 2 ) ( 1 1 2 2 variance Sample ε = s deviation) (standard 91 . 2 48 . 8 2 = = s s
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1. Characterization of Data
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1. Characterization of Data Data distribution
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1. Characterization of Data Summary o The experimental mean: o The Sample variance: = = 0 ) ( x e x F x x = = 0 2 2 ) ( ) ( x x F x x s
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Counting Statistics and Error Prediction 2. Statistical Models
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This note was uploaded on 12/10/2011 for the course ENU 4612c taught by Professor Ghita during the Fall '11 term at University of Florida.

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Lecture5 - ENU 4612C/5615C Nuclear Radiation Detection and...

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