When the first proof of 392 pages of a book of 1200 pages were
read , the distribution of printing mistakes were found to be as
follows
No of mistakes in a page (x) 0 1 2 3 4 5
No of pages (f) 275 72 30 7 5 2
Fit a Poisson distribution to the above data and test the goodness of
The PDF for the poisson distribution is
Where "\\lambda" is the mean. We equate the sample and population moments for the mean to obtain the parameter for the distribution
Therefore
"=\\frac{183}{391} =0.4680"
Since "E(X)=\\lambda=0.4680"
The PDF is therefore
Given the 391 pages, the expected frequency for the number of errors based on the poisson distribution is
"X=1: 391* \\frac{e^{-0.468}0.468^1}{1!} = 114.597"
"X=2: 391* \\frac{e^{-0.468}0.468^2}{2!} = 26.816"
"X=3: 391* \\frac{e^{-0.468}0.468^3}{3!} = 4.183"
"X=4: 391* \\frac{e^{-0.468}0.468^4}{4!} = 0.489"
"X=5: 391* \\frac{e^{-0.468}0.468^5}{5!} = 0.046"
We use the chi square test for the goodness of fit
"=\\frac{(275-244.865)^2}{244.865} + \\frac{(72-114.597)^2}{114.597} + \\frac{(30-26.816)^2}{26.816} + \\frac{(7-4.183)^2}{4.183} + \\frac{(5-0.489)^2}{0.489} + \\frac{(2-0.046)^2}{0.046}"
Since the sample size is greater than 200,(i.e. 391 pages were evaluated) the chi square critical value given a level of significance of 0.05 is
"X^2 _{critical\\ value}=233.994"
We conclude that the model is a good fit since the calculated "X^2: 146.434 < X^2 _{critical}"
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