Lecture 7: Poisson Distribution - Astronomybelz/phys3719/lecture07.pdf2 February 2011 Physics 3719...

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Lecture 7: Poisson Distribution Physics 3719 Spring Semester 2011 Simon Denis Poisson (1781-1840)

Transcript of Lecture 7: Poisson Distribution - Astronomybelz/phys3719/lecture07.pdf2 February 2011 Physics 3719...

Page 1: Lecture 7: Poisson Distribution - Astronomybelz/phys3719/lecture07.pdf2 February 2011 Physics 3719 Lecture 7 The 3 (most?) Important Probability Distributions Binomial: Result of experiment

Lecture 7: Poisson Distribution

Physics 3719Spring Semester 2011

Simon Denis Poisson(1781-1840)

Page 2: Lecture 7: Poisson Distribution - Astronomybelz/phys3719/lecture07.pdf2 February 2011 Physics 3719 Lecture 7 The 3 (most?) Important Probability Distributions Binomial: Result of experiment

2 February 2011 Physics 3719 Lecture 7

Review: Experimental and Parent Distributions

● Measure: experimental

● Infer: parent

● Physics is in the parent distribution

● Probability distribution: Normalized probability of finding event in a given bin.

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The 3 (most?) Important Probability Distributions

● Binomial: Result of experiment can be described as the yes/no or success/failure outcome of a trial. The probability of obtaining success is known.

● Poisson: Predicts outcome of “counting experiments” where the expected number of counts is small. (Special case of binomial.)

● Gaussian: Predicts outcome of “counting experiments” where the expected number of counts is large. (Special case of binomial.)

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Important Distributions

● Binomial

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Discussion

● Can radioactivity counting experiment be treated as a binomial distribution problem?

● What are some practical difficulties one might encounter in doing so?

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Poisson Distribution

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Binomial Distribution

Poisson Distribution

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Example of Poisson Distribution

● Poisson distributed data can take on discrete integer values.

● n must be an integer

● need not be!

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Example: Suppose there are 30,000 University of Utah students of which 400 carry concealed weapons permits. If JB is teaching an astronomy class of 120 students, what is the probability that one or more is packing?

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Example: Counting Experiments (Lab #2)

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Explain: Using a Geiger counter, I measure the activity of a weakly radioactive rock. I record a small number (<5) counts in a ten second interval.

Why do I expect the number of counts I'd measure in repeated trials to be Poisson Distributed?

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Example: The background radiation rate as measured in a particular room with a particular Geiger counter is known to be 1800 counts per hour.

a) If I run the Geiger counter in the room for a five second interval, how many counts do I expect to see?b) What is my uncertainty for the number of expected counts in five seconds? c) What is the probability of measuring 0 counts in 5 seconds? 1 count? 2 or more counts?

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Example: The background radiation rate as measured in a particular room with a particular Geiger counter is known to be 1800 counts per hour.

a) If I run the counter for 100 1-second long trials, how many trials do I expect to result in zero counts? b) What is the uncertainty in the number of zero count trials?

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Example: Assuming negligible uncertainty in timing, how many counts are required to measure a rate with 0.1% precision?

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Example: Now, suppose your timer has a random uncertainty of 0.05%. In this case, how many counts are required to measure a rate with 0.1% precision?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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What Happens as Becomes Large?

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Binomial Distribution

Poisson Distribution

Gaussian (Normal)Distribution

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Additional Reading and Problems

● Read in Taylor: – Ch 5: The Normal

Distribution (Sections 1 and 2)

– Chapter 10: The Binomial Distribution

– Ch 11: The Poisson Distribution

● Try the problems:– 5.4, 5.6, 5.12– 10.9, 10.10, 10.11,

10.20, 10.21, 10.22– 11.1, 11.3, 11.8,

11.10, 11.14, 11.18, 11.20