Calculation of Mixture Statistics Using Popstats - Promega

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Big Number Names: • 1,000,000 million • 1,000,000,000 billion • 1,000,000,000,000 trillion • 1 x 10 15 quadrillion • 1 x 10 18 quintillion • 1 x 10 21 sextillion • 1 x 10 24 septillion • 1 x 10 27 octillion • 1 x 10 30 nonillion • 1 x 10 33 decillion
In this case it is even less likely Based on the Hispanic population data available, the observed mixture profile is greater than 4 octillion times more likely to occur under the scenario that it is a mixture of DNA from the victim and the suspect, as opposed to the scenario that it originated from a mixture of DNA from two unrelated, unknown persons.
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Popstats Unplugged 14 th Internatio
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What Constitutes a DNA Mixture? Pr
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What Constitutes a DNA Mixture? Ci
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Common Mixture Interpretations Alle
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But, before we begin… Calculation
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Two common questions are generally
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Exclusion Probability This is a mea
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For example: Exclusion Probability
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Exclusion Probability The probabili
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Exclusion Probability In presence o
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Exclusion Probability What does thi
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We have the following data: Mixture
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Given that both victim and suspect
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What if we couldn’t assume H-W? P
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How does PopStats handle this calcu
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Here is the input data But what is
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It is the compliment of Inclusion P
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PE = 1 - 8.033 X 10 -7 = 0.99999919
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What if we have to consider some al
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Mixtures and Likelihood Ratios Like
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Let’s use the same example used i
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Three Alleles Victim is heterozygot
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The prosecution may postulate that
Page 48 and 49: The defense might argue that the fo
Page 52 and 53: Since the victim has the profile (8
Page 54 and 55: Now here is where the “RATIO” i
Page 56 and 57: Defense hypothesis 2 is a little mo
Page 58 and 59: How do we get these probabilities?
Page 60 and 61: Of course…we could incorporate θ
Page 62 and 63: What next… The total probability
Page 64 and 65: HOW TO EXPRESS THE NUMBERS FROM LIK
Page 66 and 67: Conservative Basic True!
Page 68 and 69: Or The probability (chance) that th
Page 70 and 71: Assumptions In Likelihood Computati
Page 72 and 73: Assumptions In Likelihood Computati
Page 74 and 75: So, lets go back to our previous da
Page 76 and 77: And our "K1" and "K2" genotypes:
Page 78 and 79: Our entry data from before:
Page 80 and 81: This side will autofill when changi
Page 82 and 83: C2 reflects the H a H a = The resul
Page 84 and 85: Notes: • The layout screen is pos
Page 86 and 87: Ok… so what do we get when we pus
Page 88 and 89: Big Number Names: • 1,000,000 mil
Page 90 and 91: You could also look at what the all
Page 92 and 93: C2 reflects the H a H a = The resul
Page 94 and 95: You can drag and drop the entire fi
Page 96 and 97: Continue, holding the SHIFT button
Page 100 and 101: Lets look at a different scenario O
Page 102 and 103: Two alleles match the suspect - A 1
Page 104 and 105: The prosecution may postulate that
Page 108 and 109: The resulting likelihood ratio is:
Page 110 and 111: So, with regard to Defense Hypothes
Page 112 and 113: Same question as before but… Thre
Page 114 and 115: Under the Prosecution’s hypothesi
Page 116 and 117: Unk 1 Unk 2 A1A2 A1A2 A1A2 A1A3 A1A
Page 118 and 119: The Likelihood Ratio becomes: p 3 2
Page 120 and 121: p 1 = 0.1, p 2 = 0.2, and p 3 = 0.3
Page 122 and 123: So, with regard to the Defense Hypo
Page 124 and 125: Of course we can do this in PopStat
Page 126 and 127: Of course we can do this in PopStat
Page 128 and 129: Now…Let's have some real fun! Sce
Page 130 and 131: Our Knowns: Let's see how this scen
Page 132 and 133: H a1 = The results are explained by
Page 134 and 135: Our Results:
Page 136 and 137: The "profile" in C1 represents all
Page 138 and 139: Our Results:
Page 140 and 141: Considerations Unlike interpretatio
Page 142: Considerations Most critical step o
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Calculation of Mixture Statistics Using Popstats - Promega

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