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I"m trying to plot an OC curve (y-axis Probability of acceptance, x-axis Lot Percent Defective) and there should be a way to plot using a hypergeometric distribution.

In[117]:= NProbability[x <= 0, 
 x \[Distributed] HypergeometricDistribution[8, 7, 500]]

Out[117]= 0.89262

is great for one point. The 7 in the distribution is the number defective in the lot of 500, I'd like to plot this for 1, 2, etc. Then alter the x-axis labels to represent the percent defective in the lot of 500, .1%, 1%, 2%, etc....

I can get the individual values as above, yet not able to get a plot.

I can do this using PoissonDistribution

Plot[{N[Probability[x <= 0, 
    x \[Distributed] PoissonDistribution[13*lpd]]], 
  N[Probability[x <= 0, 
    x \[Distributed] PoissonDistribution[8*lpd]]]}, {lpd, 0, .5}]

which assumes a very large lot size. I have the situation with smaller lot sizes and using hypergeometric is the right way to do the calculation for the OC curve - just not able to sort out the plotting.

Any suggestions?

cheers,

Fred

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DiscretePlot is good for plotting discrete functions –  ssch Feb 11 '13 at 3:55
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1 Answer 1

up vote 5 down vote accepted

With the Ticks option you can set custom ticks, see this:

DiscretePlot[
 Probability[x <= 0, x \[Distributed] HypergeometricDistribution[8, d, 500]],
 {d, 0, 250},
 Ticks -> {Table[{i 500/100, ToString@i <> "%"}, {i, 0, 50, 5}],Automatic}
]

enter image description here

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This is right on what I was trying to do. Excellent. –  Fred Schenkelberg Feb 11 '13 at 17:41
    
Ok, now is it possible to easily adjust the x-axis ticks to show correct lot percent defective when I change the number of units sampled and the lot size? I apparently do not understanding the Ticks element and how it is constructed as I'm not able to alter it and get meaningful results. cheers, Fred –  Fred Schenkelberg Apr 22 '13 at 18:24
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