Calculating the Chi Squared Value from Bacterial Enumerations

Calculating the Chi Squared Value from Bacterial Enumerations

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A normal distribution will overestimate the true average for a small sample size from a randomly distributed population. This is why the geometric mean is used to estimate the true average of Poisson distributed populations. Observe the figure bellow: the green bar is the average of the Poisson Distribution, and the red bar is the average of a normal distribution. A Poisson Distribution is used to describe count data that is distributed randomly. Examples of random counts are radioactive disintegrations per minute, numbers of moths found per tree, and other discrete events. Bacteria are generally thought to be distributed randomly, or as a Poisson distribution, not distributed evenly throughout a matrix. If very few samples of a randomly distributed population are taken (<19 samples) then a Poisson distribution more accurately represents the actual distribution of the population than a standard normal, or Gaussian distribution and the geometric mean should be used to estimate the true mean of the sample, not the arithmetic mean. Observe the figures below
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This note was uploaded on 03/18/2010 for the course CE 555 taught by Professor Dr.brion during the Fall '09 term at Kentucky.

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Calculating the Chi Squared Value from Bacterial Enumerations

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