Opinion ID: 1830839
Heading Depth: 1
Heading Rank: 19

Heading: Whether the Circuit Court erred in allowing the Appellee to introduce into evidence census data for Mississippi.

Text: ¶ 104. Hughes seeks reversal on the basis that trial court improperly allowed the statistical census data regarding the population of Mississippi to be admitted into evidence over his objection that it was irrelevant and highly prejudicial under M.R.E. 401, 402 and 403. ¶ 105. This Court in Hull v. State stated that the frequency with which a given match occurs randomly in the population is relevant and admissible evidence in an RFLP case, and it likewise should also be admitted in the context of PCR. Hull v. State, 687 So.2d 708, 728 (Miss.1996) ¶ 106. The State introduced as a general exhibit to its case three sets of population statistics. One set of data gave a population breakdown by gender of those persons living in rural, suburban and urban areas of Mississippi. A second set of data gave a population breakdown of all persons in Mississippi by age, gender and race. These first two sets of data were contained in a total of two pages. ¶ 107. A third set of data included population statistics from the following counties: Alcorn, Benton, Bolivar, Calhoun, Chickasaw, Coahoma, DeSoto, Grenada, Itawamba, Lafayette, Lee, Marshall, Monroe, Panola, Pontotoc, Prentiss, Tallahatchie, Tate, Tippah, Tishomingo, Tunica, Sunflower, Union, Quitman and Yalobusha. This data was broken down by gender, age and race [6] for each county. This set of data was contained in a total of forty pages. ¶ 108. Hughes contends the inclusion of this mass of statistical data skewed the value of the DNA evidence against him. The State's expert testified at length about the DNA evidence and the likelihood that matching DNA could be found in the population at large. ¶ 109. It is critical to understand some fundamental concepts about probability in order to properly weight DNA frequency statistics. Logical errors are very common in this area and routinely made by the attorneys and experts attempting to present DNA statistical evidence. [7] ¶ 110. A frequency statement such as 1 in 86,000 is not a statement of the probability that some other person besides the defendant has the same DNA match. The statistic of 1 in 86,000 refers to the probability that a random person picked from the reference population group would have consistent DNA. The reference population upon which the State's expert based its statistics was the general population of the United States. Thus, while the statement 1 in 86,000 persons share Hughes' DNA is correct, the statement that we must therefore test at least 86,000 persons to find another consistent match is a logical fallacy. The correct statement would be that If we were to test every single member of the reference population, the average occurrence of this genotype would be 1 in 86,000. Necessarily, such a calculation does not speak in absolute terms but in averages. ¶ 111. Mrs. Montgomery, the State's DNA expert and defense counsel essentially made this mistake when discussing the statistical probability during voir dire prior to trial. Q. [COUNSEL FOR HUGHES ON CROSS] Assume, Mrs. Montgomery, that on the facts I mentioned, that the State alleges the crime occurred in Tate County, Mississippi, and at the 1990 census Tate County had a population of 21,432 individuals. Now, would it be fair to argue that you would have to test, for example, four Tate Counties? A. MRS. MONTGOMERY [Witness] Well, I would need to know the race breakout of that 21,000 because we look at these frequencies based on racial populations. Q. Right. A. And if you're adding up numbers that's oneI would do it as casting a net. If you had to cast a net to find how many peopleand I'm saying, say, 86,000 individuals I need to look atyou would need to cast a net big enough to cover 86,000 folks, to look at those folks and profile them. Q. So that would be Tate County four times? You've have to cast four nets? A. Utilizing your numbers and assuming one race group. Q. Right. A. Basically, I guess. Q. So your answer would be yes? A. Yes. ¶ 112. Clearly, a 1 in 86,000 random match probability (RMP) does not equate to having to test four (4) Tate Counties to find a match, as was posited by the defense attorney and accepted by Mrs. Montgomery. One theoretically could randomly find a match sitting in the courtroom, or two matches within one building in Senatobia, Mississippi, whether the population of Tate County was 10 or 1,000,000 people. However, it is important to note that this analogy was not made before the jury either in questioning of the State's expert or in argument at closing. ¶ 113. Obviously, applying a RMP of 1 in 86,000 to a greater base population will result in a higher probability of someone else within that population having a match because you would, theoretically, be testing a larger group of persons; and, therefore, you would have more chances of getting a positive match. Concomitantly, the same is true that if the base probability of a random match is 1 in 86,000 over the whole Southeast, then testing a smaller reference population, such as Tate County, would yield a lower probability of a match in the reduced population set. This concept is often employed by defense attorneys when the population in the area in which the crime occurred is substantially higher than the RMP. This general concept was noted by Mrs. Montgomery when she testified: A. [MRS. MONTGOMERY ON DIRECT] Well, I think it's important because I think some lay individuals think DNA is absolute identity. And at present, given the testing systems we're running, I could not say absolute identity. In the future we may be able to but today we cannot and we should not. And so when you're talking about a profile it's important to know how common or how rare it is so that you can say, all right, if it's a very common profile, if it's 1 in 4, then 1 in 4 people could have been the donor. Well, then now you know how heavily to weigh that as opposed to 1 in a million or 1 in a billion or 1 in 86,000. And again, I think other things should be considered. You've brought up geography. One in 86,000 may mean one thing in Los Angeles or New York and another thing in Louisiana or Mississippi. But I feel the jury or the Court should made that decision, not me. ¶ 114. While this is true in the abstract, and certainly goes to the weight of the statistic, the math involved in putting a definite number on the difference in 1 in 86,000 in Los Angeles and 1 in 86,000 in Tate County is quite complex. [8] This entire hypothesis of cause assumes a random distribution across the reference population of the various genotypes. The possibility of groupings of certain genotypes based on ethnic subpopulations (substructuring) was once a hotly debated topic, but has largely been resolved with advent of the National Research Council Committee Report II (NRC II). [9] ¶ 115. The odds are definitely against finding a match in Tate County86,000 to 1, which is what the statistic properly means. But, the important fact is that the number 86,000 in this odds calculation does not represent a given sample number which must be tested in order to find consistent DNA. However, during her testimony, Mrs. Montgomery was careful to note the correct use of the statistic before the jury and steered clear of linking the frequency estimate of 1 in 86,000 to any absolute statistical probability that Hughes was in fact the matching donor. A. [MRS. MONTGOMERY ON DIRECT] [D]epending on the markers, some people refer to PCR as an exclusionary test, in that you can exclude an individual with 100% assurance but when you say you can't exclude that individual because his genetic markers are consistent with the biological evidence, you're not saying he donated that sample, you're saying that you cannot exclude him as a donor. And then the next question becomes, well, maybe if it's not him, who else could it have been. Then you go to the frequency charts on how common or how rare these genetic markers are to find out whatever your profile is what is the frequency. If I looked at a population of individuals, how many people would I have to look at on average to find another individual who would be the same as the biological sample profile that we looked at. ¶ 116. 1 in 86,000 is simply not that strong a statistic, standing on its own. Clearly, the State can and should point out to the jury that the frequency of random occurrence, coupled with the non-statistical, circumstantial evidence of this case, make it highly unlikely that another man besides Mr. Hughes is the match for the DNA found in the semen, and this was done by the State, albeit while mis-characterizing the nature of the frequency statistic: [Prosecutor during closing argument] What she [Mrs. Montgomery] told you [was] that the sperm found in Ashley Galloway was of a genetic profile so rare that it only appeared in 86,000 people, one in every 86,000 people, okay, and William Ray Hughes is one of those people that share that profile, okay? She told you you'd have to drop a big net, drop it across the country, drop a big net, pull 86,000 people at random in order to find one other person that shares the same genetic profile as the one who left that sperm and the same as William Ray Hughes. You know, that's what we call a statistical probability, ladies and gentlemen. But I want to ask you to think a little further. Use your common sense, okay? That's what we keep telling you. Suppose we were to find another person that shared that same genetic profile. Suppose we were to test 86,000 and find one other who shared that same genetic profile. Wonder if that one person would happen to drive a black truck. Wonder what the statistical probability of that might be. I wonder whether that one other person that you might find out of 86,000 might also work 1.2 miles from the place that Ashley was picked up, having left work just minutes before she got into a car matching the description. Wonder what the statistics would be on that. What do you suppose the probability would be? And if we found another person who shared that genetic profile when we pulled those 86,000 people at random, wonder what the probabilities would be of them having one of Ashley's rings at their front door. Do you see what I'm saying to you, ladies and gentlemen? In a case such as this you cannot isolate the circumstances. If there was just one point of proof, ladies and gentlemen, maybe that would not be enough for you. Maybe there would be reasonable doubt, but what you just do in a case like this is look at the totality of the circumstances, and the DNA is but one of those circumstances that you must look at, you must focus on. It's one of those things that brings us to William Ray Hughes as the one who raped and murdered Ashley. I wonder if we found another one person in that 86,000 in a random pull whether or not Stella Rowe would have said, yes, that's the man. ¶ 117. This unquantified inference, however, is fundamentally different than stating that the statistics, in the absence of the circumstantial evidence linking Hughes to the victim's property and last known location, can demonstrate that Hughes must be the matching donor of the DNA simply because, given the frequency of occurrence, no other person in this area could have this DNA. However, this was not done. We still have the census data from the State of Mississippi which was received into evidence and is there, a mass of information which is irrelevant. ¶ 118. In different contexts this Court has held one erroneous or confusing item in a mass of information submitted to the jury is not enough to warrant reversal. Motorola Communications & Elecs., Inc. v. Wilkerson, 555 So.2d 713, 722 (Miss. 1989). In Wilkerson, thirty-three (33) out of fifty-four (54) requested jury instructions were approved and submitted to the jury. One instruction was found on appeal to be confusing. It combine[d] testimony and statutory language in such a way that it seem[ed] to be a comment on the evidence and [it] is doubtful that the instruction was helpful to the jury; therefore, it should not have been given. Wilkerson, 555 So.2d at 722. Even though the Court found the instruction to be an erroneous statement of law and confusing to the jury, the Court focused on the importance of viewing everything submitted to the jury as a whole. The Court found it highly unlikely one item out of so many would, by itself, cause the jury to render a verdict against a defendant. ¶ 119. The reasoning in Wilkerson applies here. The Hughes jury listened to lengthy expert testimony concerning the DNA evidence in this case. The State submitted forty-four (44) pages of highly detailed statistical evidence as part of a general exhibit. Neither the State nor the defense commented on the statistics submitted. This data was not helpful and should not have been admitted. It is unbelievable, however, that the jury could have pulled one single item out of this mass of information, as Hughes suggests, and rendered its verdict based solely on this exhibit. This proposition is strengthened by the overwhelming evidence from other sources that Hughes committed this rape and murder. Even though the population data should not have been admitted, this alone is not enough to warrant a reversal. ¶ 120. We find the admission of census data in the abstract to be harmless error.