Minor fix for PR
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@ -16,8 +16,7 @@ If you take the pointwise mixture of two distributions with very different means
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In the following case, the mean of the mixture should be equal to the sum of the means of the parts. These are shown as the first two displayed variables. These variables diverge as the underlying distributions change.
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In the following case, the mean of the mixture should be equal to the sum of the means of the parts. These are shown as the first two displayed variables. These variables diverge as the underlying distributions change.
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<SquiggleEditor
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<SquiggleEditor
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initialSquiggleString={
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initialSquiggleString={`dist1 = {value: normal(1,1), weight: 1}
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`dist1 = {value: normal(1,1), weight: 1}
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dist2 = {value: normal(100000000000,1), weight: 1}
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dist2 = {value: normal(100000000000,1), weight: 1}
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totalWeight = dist1.weight + dist2.weight
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totalWeight = dist1.weight + dist2.weight
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distMixture = mixture(dist1.value, dist2.value, [dist1.weight, dist2.weight])
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distMixture = mixture(dist1.value, dist2.value, [dist1.weight, dist2.weight])
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@ -30,10 +29,8 @@ separateMeansCombined = (mean(dist1.value) * (dist1.weight) + mean(dist2.value)
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The means of sample set distributions can vary dramatically, especially as the numbers get high.
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The means of sample set distributions can vary dramatically, especially as the numbers get high.
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<SquiggleEditor
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<SquiggleEditor
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initialSquiggleString={
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initialSquiggleString={`symbolicDist = 5 to 50333333
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`symbolicDist = 5 to 50333333
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sampleSetDist = toSampleSet(symbolicDist)
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symbolicSetDist = toSampleSet(symbolicDist)
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[mean(symbolicDist), mean(sampleSetDist), symbolicDist, sampleSetDist]`}
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[mean(symbolicDist), mean(symbolicSetDist), symbolicDist, symbolicSetDist]`}
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/>
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/>
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