Case ID: sw2d_976/html/0241-01.html
Source: Caselaw Access Project
Author: {"author": "DODSON, Justice. QUINN, Justice,", "license": "Public Domain", "url": "https://static.case.law/"}
Date Created: 2024-08-24T03:29:51.129683

Russell Alan GRIFFITH, Appellant, v. The STATE of Texas, Appellee.
    No. 07-96-0140-CR.
    Court of Appeals of Texas, Amarillo.
    June 9, 1998.
    Discretionary Review Refused Oct. 14, 1998.
    
      Chappell & Lanehart, P.C., Chuck Lane-hart, Lubbock, for appellant.
    William Sowder, Crim. Dist. Atty., Michael West, Lubbock, for appellee.
    Before BOYD, C.J., and DODSON and QUINN, JJ.
   DODSON, Justice.

In a jury trial, appellant Russell Alan Griffith was convicted of sexual assault. The jury assessed his punishment at confinement for twenty years in the Texas Department of Criminal Justice, Institutional Division. By three points of error, appellant contends the trial court erred in admitting State’s evidence regarding DNA testing involving a probability of paternity statistic using Bayes’ Theorem as violating the presumption of innocence, or in the alternative, the trial court erred in admitting such evidence without testimony on the mathematical applications of the test results, and that the court erred in overruling his motion to set aside the verdict and judgment where the prosecution introduced inadmissible evidence clearly calculated to inflame the minds of the jury. Affirmed.

On July 17, 1989, the staff of the Lubbock State School (the School) had a female patient, T.S., examined because of abdominal swelling. T.S. was a profoundly retarded female client in her early thirties. With an I.Q. of 11, T.S. had the mental capacity of a two year old child, and had very diminished communication skills. She was therefore unable to tell anyone that she had been assaulted. An x-ray revealed that T.S. was pregnant. Further diagnosis placed the date of conception between February 7, 1989 and March 27, 1989. A child was born on December 7,1989.

After approximately one year, School officials notified the police when they began to suspect that an employee may have been the father. Prior to that time, the School believed that the father was probably one of the male clients at the School.

Appellant started work at the School as a direct care worker in August, 1988. Appellant worked in the restricted access dormitories on the night shift from 10 p.m. to 6 a.m. After reviewing sign-in logs, police determined that five male direct-care workers, including appellant, had access to T.S. between the dates of the estimated conception. Blood samples from T.S., the baby, and the five male suspects were sent to the University of North Texas Health Science Center in Fort Worth for DNA testing.

Dr. Arthur J. Eisenberg, the administrator of the lab, testified as a State’s witness at trial. The DNA test results excluded four of the five male direct-care workers from being the father of the child. Appellant was not excluded. Dr. Eisenberg testified that three different statistical values were generated from appellant’s DNA test results. One of those statistics, the probability of paternity, was challenged by the defense. A hearing on a motion to suppress this evidence was had, and the trial court overruled the motion. The evidence was then admitted before the jury which convicted him of sexual assault and sentenced him to twenty years in the Texas Department of Criminal Justice, Institutional Division. Appellant timely filed a motion for new trial, which was denied. This appeal followed.

Appellant’s First Point of Error

In his first point of error, appellant complains that the trial court erred in admitting testimony regarding DNA testing, specifically the probability of paternity statistic based on Bayes’ Theorem, because the calculation was based on a presumption of guilt. Under this point of error, appellant contends that the use of Bayes’ Theorem to calculate the probability of paternity statistic permitted the State to convict him without meeting its burden of proof. Specifically, he says that the use of the Bayes’ Theorem to calculate the probability of paternity statistic assumes a fact for which there is no independent proof — i.e., that he had sex with the complainant. Appellant limits his challenge to the DNA evidence admitted at trial to the probability of paternity statistic calculated by the use of Bayes’ Theorem. The remaining DNA evidence in the record is unchallenged.

The record shows that there are two possible results from a DNA paternity test. Either a potential father is excluded, meaning he is shown to not be the father, or he is included. If the male is excluded from paternity by the test, no statistics are generated. If the male is included, the results are not absolutely conclusive that he is the father and there remains a chance or possibility that he is not the father, even though that possibility in some instances may be very de minimis. This possibility is stated statistically. Nevertheless, only the biological father’s test results will match the child’s test results. When the male is included, as appellant in this instance, the test results are reduced to statistical figures derived from all frequencies assigned to each chromosome region tested (i.e., six in this instance). The statistical values are reported in three ways: the paternity index, the probability of exclusion, and the probability of paternity.

The paternity index is a value reflecting the likelihood that a tested man is the father of the child as opposed to an untested man of the same race. It is expressed in a number. If a paternity index can be assigned to a man, it means that he is that many more times likely to be the father than any other randomly selected male of his race. Paternity index is determined by multiplying together all of the allele frequencies (rate of occurrence) for each region tested.

The probability of exclusión considers the DNA of the mother and the child. This number is a percentage. Since half of a child’s DNA comes from each parent, by comparing the DNA of the mother and the child, then excluding the DNA that matches, the remaining DNA of the child necessarily belongs to the father. This number reflects the strength of the DNA test, by showing the percentage of the male population that would have been excluded by the test.

Finally, DNA test results can be expressed as a probability of paternity. This number is also a percentage. This statistic is calculated using Bayes’ Theorem, a mathematical formula in which probabilities are associated with individual events and not merely with random sequences of events. Webster’s New Collegiate Dictionary 95 (1981). Bayes’ Theorem is necessary to convert probabilities into percentages. The formula is stated as follows:

See M. v. Marvin S., 173 Misc.2d 925, 656 N.Y.S.2d 802, 806 n. 4 (Fam.Ct.1997); State v. Skipper, 228 Conn. 610, 637 A.2d 1101, 1104 (1994). The resulting percentage reflects the percent likelihood that the tested male is actually the father of the child. The formula requires the use of a prior probability of an event occurring.

The Test and the Results

After the police collected blood samples from the mother, the child, and the five male suspects, the samples were sent to the University of North Texas Health Science Center at Fort Worth where DNA tests were run. Dr. Eisenberg testified about the results of the tests and the resulting statistical analysis. Initially, four DNA regions, or loci, were tested. Three men did not match at any tested region. One man matched at only one region. Accordingly, these four men were excluded from paternity. The fifth man, appellant, matched at all four tested regions. Dr. Eisenberg testified that two additional genetic regions were tested. Appellant matched in both, bringing the total to six matches. Since the other four men were excluded, no statistics were generated on them.

Statistics as to appellant’s results were generated. Appellant’s paternity index was lk,961 (indicating he was 14,961 times more likely to be the father than a randomly selected male of Ms race). The 'probability of exclusion was “in excess” of 99.99% (the test would have excluded more than 9,999 men of every 10,000 tested). The probability of paternity was “in excess” of 99.99% (the likelihood that appellant was the father of the child was Mgher than 99.99%). It is this third statistical figure that appellant challenges.

Admissibility of the Challenged Evidence

We are persuaded that the admissibility of the challenged evidence is controlled by the Court of Criminal Appeals’ determination in Kelly v. State, 824 S.W.2d 568 (Tex.Cr.App.1992). In Kelly, the court delineated the standard for the admissibility of novel scientific evidence. Before admitting such evidence, a trial court must make the “threshold determination” as to whether the testimony will help the fact trier understand the evidence or determine a fact in issue. Thus, when the trial court is faced with a proffer of expert testimony or a scientific topic unfamiliar to lay jurors, the trial court’s first task is to determine whether the testimony is sufficiently reliable and relevant to help the jury in reaching accurate results. Id. at 572. If the trial court determines that the proffered expert testimony is rehable (i.e., probative and relevant), the trial court must next determine whether the proffered testimony might nevertheless be un helpful to the fact triers for other reasons, such as if it is merely cumulative or would confuse or mislead the jury, or would consume an inordinate amount of trial time. In essence, if the trial court determines that the proffered expert testimony is rehable and relevant, the court must still determine whether the probative value of the evidence is outweighed by one or more of the factors in Rule 408 of the Texas Rules of Evidence. Id.

The Court of Criminal Appeals further explained how the reliability prong of the test of admissibility should be met. For scientific evidence to be considered reliable, it must satisfy three criteria. First, the underlying scientific theory must be vahd. Next, the technique applying the theory must be vahd. Finally, the technique must have been properly applied on the occasion in question. Id. at 573.

These three criteria must be shown by clear and convincing evidence outside the presence of the jury. Id. Factors that could affect the trial court’s determination include, but are not limited to the following: the extent to wMch the underlying scientific theory and technique are accepted as vahd by the relevant scientific commumty, the qualifications of the expert testifying, the existence of literature supporting or rejecting the underlying scientific theory and technique, the potential rate of error in the technique, the availability of other experts to test and evaluate the technique, the clarity with which the underlying scientific theory and technique can be explained to the court, and the experience and skill of the persons who applied the technique on the occasion in question. Id.

The Kelly court summarized its determination as follows:

To summarize, under Rule 702 the proponent of novel scientific evidence must prove to the trial court, by clear and convincing evidence and outside the presence of the jury, that the proffered evidence is relevant. If the trial court is so persuaded, then the evidence should be admitted for the jury’s consideration, unless the trial court determines that the probative value of the evidence is outweighed by some factor identified in Rule íOS. (Emphasis added.)

When the admission of such evidence is challenged on appeal, the question is whether the trial court abused its discretion by admitting the evidence.

In the case before us, appellant does not challenge the admissibility of the DNA testing, nor does he attack two of the three statistics generated from the test results. We note that in Kelly, the Court of Criminal Appeals addressed for the first time whether RFLP (restriction fragment length polymor-pMsm) DNA testing was admissible in a criminal trial. Applying the newly announced rule, the Court concluded such testing was admissible. Id. at 574.

In this instance, appellant challenges the probability of paternity statistic calculated from the DNA test results. We conclude that the probability of paternity statistic meets the Kelly admissibility requirements and that the trial court did not abuse its discretion in admitting the challenged evidence.

The trial court conducted a hearing outside the presence of the jury to determine the admissibility of the State’s DNA evidence. The State’s expert, Dr. Arthur J. Eisenberg, testified about the DNA evidence generally and the probability of paternity statistic in particular. Dr. Eisenberg has a Bachelor’s of Science in Biology, a Master’s of Science in molecular biology, and a Ph.D. in molecular biology. He listed a number of organizations he belongs to involved in DNA testing or research including the American Association of Blood Banks, the U.S. DNA Advisory Board, and the Parentage Testing Committee. Further, he testified that he had been involved in the field of DNA testing since its inception. Eisenberg set up and manages the DNA laboratory at the University of North Texas at Fort Worth where the testing in this case was performed.

Eisenberg testified that in this case he conducted a paternity test on five males, T.S., and the baby. Appellant was one of those five, and he was the only one not excluded from paternity by the DNA testing. Eisenberg stated unequivocally that the methodologies used for statistical analysis of the test results were “standard methods” employed in over 200,000 parentage tests performed nationwide annually.

Eisenberg explained each of the three statistics in turn. The probability of paternity was calculated by using Bayes’ Theorem. Bayes’ Theorem, according to Eisenberg, states that prior to the testing, there is a prior probability of paternity. He stated

that courts in the United States typically use a .5 or 50% prior probability because it is a neutral probability. The .5 prior probability indicates that the tested male either is or is not the father. Eisenberg further testified that this calculation was a generally accepted principle, and was standard methodology in parentage testing, having been used for twenty or thirty years.

Eisenberg further explained the theory and methodology involved in DNA testing generally. After explaining how DNA functions and how the tests are conducted, he discussed the specific results in this case. Eisenberg stated that using the .5 prior probability, which was the standard prior probability reported in parentage tests, that appellant’s probability of paternity was 99.99%. At this point, the State passed Eisen-berg as a witness, and defense counsel cross-examined him.

On cross, Eisenberg reiterated that the prior probability of .5 was a neutral prior probability which did not presume appellant was guilty of the crime or more likely than not guilty. He emphasized that he had personally testified in both civil and criminal paternity matters using the same statistic invoking a .5 prior probability. Eisenberg stated that he had testified in over a dozen Texas criminal cases involving paternity issues where he used the .5 prior probability.

Most notably, Dr. Eisenberg was asked point blank whether he saw any problem using the .5 prior probability in a criminal case, even assuming the defendant as presumed to be innocent. Eisenberg’s answer, twice, was “[ajbsolutely not.” He testified that the .5 prior probability did not unfairly skew the probability of paternity statistic. Moreover, Eisenberg stated that if a lower prior probability number had been used, like .1, then the probability of paternity statistic would have been lower, though it would still be representative of the fact that the appellant had matched at six genetic test sites. According to Eisenberg, if a prior probability that reflected true parentage testing had been used, it would have been something higher than .5 and the probability of paternity would have been even higher than 99.99%.

Based on Dr. Eisenberg’s testimony, the trial court was required to determine whether the State had shown by clear and convincing evidence that the probability of paternity statistic would be helpful to the trier of fact and that it was sufficiently reliable and relevant to help the jury in reaching accurate results. Looking to the factors outlined in Kelly, we note that Eisenberg testified that hundreds of thousands of DNA tests, and millions of HLA and DNA tests around the nation reported paternity results using Bayes’ Theorem and the probability of paternity invoking a .5 prior probability. These tests were conducted by accredited testing facilities, and the statistical calculation was “standard.”

Eisenberg testified about his qualifications in DNA paternity testing and reported that he was involved in the field from its inception. He testified that the statistical calculation was employed for twenty to thirty years in paternity tests based on HLA blood typing and later DNA analysis. Eisenberg commented that there were over fifty other laboratories in the country using the same techniques and reporting the same statistics. He also stated that the calculations employed in this particular test were the “standard” method of reporting paternity results around the country. Finally, he testified about the techniques involved in DNA testing, his qualifications in conducting those tests, and his experience in reporting statistics, which were “co-related” to the DNA testing.

Based on Eisenberg’s testimony, the trial court clearly recognized that the Bayes’ Theorem calculation was commonly used in reporting DNA paternity results. Moreover, it is clear that the probability of paternity statistic is accepted in the scientific community of molecular biology in reporting paternity results. Eisenberg stated that he used the same calculation used in thousands of other tests, indicating that he properly invoked the reporting method. Likewise, there was no challenge that he did the math improperly. We conclude that this evidence was clear and convincing in showing that the probability of paternity statistic was valid, the technique applying the statistic was valid, and that it was properly applied .in this case. Thus, the trial court properly concluded that the statistic was reliable and relevant to helping the jury reach accurate results.

As to the second prong of the Kelly test, there was no challenge to the evidence as being time consuming, cumulative, confusing or misleading, or otherwise more prejudicial than probative. The only challenge raised by appellant was his assertion that the statistic violates the presumption of innocence.

The Presumption of Innocence

The presumption of innocence does not appear in the U.S. or the Texas Constitutions. However, courts have recognized that the presumption of innocence is part of the 14th Amendment Due Process and 6th Amendment right to fair trial. Randle v. State, 826 S.W.2d 943, 945 n. 3 (Tex.Cr.App. 1992); Rogers v. State, 846 S.W.2d 883, 885 (Tex.App. — Beaumont 1993, no pet.). Also, the Legislature has codified the presumption of innocence in the Texas Penal Code and the Code of Criminal Procedure. See Tex. Penal Code Ann. § 2.01 (Vernon 1994); Tex.Code Crim. Proc. Ann. art. 38.03 (Vernon Supp. 1998).

It is stated that the presumption of innocence is not a true presumption. Normally, a presumption is an assumption of fact that the law requires to be made from another fact or group of facts found or otherwise established in the action, which may be re-buttable or conclusive. Black’s Law Dictionary, 1185 (6th ed.1990). A presumption acts as a burden shifting device. Id.

By contrast, the presumption of innocence is perhaps better phrased the “assumption of innocence.” McCormick on Evidence § 342 at 579-80 4th ed. (1992). It merely describes the fact that the burden of persuasion and production in a criminal matter are on the prosecution. Id. It cautions the jury to reach their conclusion solely from the evidence adduced, and not from the fact of arrest or indictment. Id. citing 9 Wigmore Evidence § 2511 at 407 (Chadbourn rev.1981).

The presumption of innocence is not a true presumption because the defendant is not required to come forward with proof of innocence once evidence of guilt is introduced so as to avoid a directed verdict of guilty. Black’s Law Dictionary, 1186 (6th ed.1990). Typically, cases finding violations of the presumption of innocence involve situations where the defendant is placed before the jury, dressed in shackles or jail clothes, or where the State offers evidence that the defendant has been indicted in other crimes. See Randle, 826 S.W.2d at 946; Lafayette v. State, 835 S.W.2d 131, 135 (Tex.App. — Texar-kana 1992, no pet.). Clearly neither of those situations exist here.

In the case before us, testimony was elicited from Dr. Eisenberg about all three statistics. Dr. Eisenberg testified on direct about probability of paternity based on a .5 prior probability. On cross, he testified about how the probability number would change based on different prior probability values. We conclude that the use of a probability of paternity statistic based on Bayes’ Theorem in a criminal proceeding does not violate the presumption of innocence. The use of a pri- or probability of .5 is a neutral assumption. The statistic merely reflects the application of a scientifically accepted mathematical theorem which in turn is an expression of the expert’s opinion testimony. It is subject to the same conditions applied to all other expert testimony. The jury is free to disregard it. It can be weakened on cross and in argument. The statistic does nothing to shift the burdert of persuasion or production in a criminal matter.

Appellant asserts that his specific challenge is a matter of first impression in Texas criminal cases. Consequently, he relies on two cases from other jurisdictions where the courts exclude the probability of paternity calculation as a violation of the presumption of innocence. While we do find eases that have admitted DNA testing and the probability of paternity statistic, we have found no Texas criminal case in which the presumption of innocence challenge was made or addressed.

The two primary cases the appellant relies on to support this alleged violation of the presumption of innocence challenges are State v. Hartman, 145 Wis.2d 1, 426 N.W.2d 320 (1988) and State v. Skipper, 228 Conn. 610, 637 A.2d 1101 (1994). The rationale in Hartman and Skipper is that the probability of paternity statistic violates the presumption of innocence because it assumes that the putative father had sexual intercourse with the mother; stated another way, it assumes the crime was committed by him in order to prove that the crime was committed by him. Hartman, 426 N.W.2d at 326; Skipper, 637 A.2d at 1106 (citing Hartman). Both of these cases come to this conclusion, at least in part, by relying on Peterson, A Few Things You Should Know About Paternity Tests (But Were Afraid To Ask), 22 Santa Clara L.Rev. 667 (1982).

Additionally, the Hartman court bases its conclusion on a single statement it made just one month earlier in In Re Paternity of M.J.B., 144 Wis.2d 638, 425 N.W.2d 404 (1988). In Hartman, the court said the assumption underlying the probability of paternity statistic was “that the mother and the putative father have engaged in sexual intercourse at least once during the possible conception.” Hartman, 426 N.W.2d at 326 (quoting M.J.B., 425 N.W.2d at 409, in turn citing Peterson, 22 Santa Clara L.Rev. at 685). For reasons we shall explain, we do not agree that the basic assumption that intercourse occurred is implicit in the statistic.

Peterson’s Santa Clara Law Review article seems to be at the root of the Hartman and Skipper decisions. That article discusses the use of blood tests in paternity cases, including HLA testing. HLA testing reports the same three statistics reported in DNA testing, and in particular in the case before us. In that article, Peterson criticizes the value of Bayes’ Theorem. He states that Bayes’ Theorem accurately reflects the odds that the accused is the father only if one assumes “that the defendant had intercourse with the mother and that a random man ... also had intercourse with her.” Peterson, Santa Clara L.Rev. at 685. We note that the author of the article was himself not a statistician or geneticist, but an attorney and professor. We farther note that the author does not cite direct authority (either legal or scientific) to support his statement. We disagree with this conclusion. Logically, the prior probability assumes intercourse could have occurred and thus the putative father could be the actual father, but the statistic does not necessarily assume intercourse did occur.

As Dr. Eisenberg testified at the suppression hearing, the .5 prior probability is “a neutral prior probability” that indicates “[either [the putative father] is or is not the father.” There was no testimony from Ei-senberg or Koehler, the defense expert, indicating that the prior probability assumes intercourse necessarily occurred. The prior assumption could invoke any number of possible conditions or permutations, as Peterson points out, including time of intercourse, frequency, fertility, and the like. However, by making the prior assumption .5 (i.e., — equally weighted), Bayes’ Theorem also allows, that intercourse may not have occurred at all.

Hartman and Skipper rely heavily on the conclusion in Peterson’s article which we consider questionable. Moreover, it is important to note that the Hartman court, while it quotes M.J.B. in part, does not follow M.J.B.’s rationale. In M.J.B., the Wisconsin Supreme Court also stated that “the probability of paternity statistic is conditionally relevant evidence; only after competent evidence is offered to show that sexual intercourse between the mother and alleged father occurred during the conceptive period may evidence of the probability of paternity statistic be received.” In Re Paternity of M.J.B., 425 N.W.2d at 409. However, the Wisconsin Supreme Court further stated:

This foundational evidence [of intercourse] may be supplied by the mother herself.... However, we note that this threshold evidence is not limited to direct testimony by the mother that she engaged in sexual intercourse with the alleged father. Evidence that the defendant has access to the mother during the conceptive period may be offered by any individual knowledgeable of the facts of their association. By ‘access’ we mean that the mother and putative father were together at a time, under circumstances and in a location which would lead a reasonable person to believe that the sexual intercourse took place between them.

Id. (emphasis added).

In the case before us, there was testimony from Lubbock police that appellant was one of the male care workers who had access to T.S.’s dormitory. Moreover, there was evidence that appellant worked the late night shift, from 10:00 p.m. to 6:00 a.m. Both the police, via the restricted access dormitory log sheets, and appellant himself, provided evidence that appellant had the opportunity to be alone in the dorm with T.S. and other patients during the conceptive period; that is, he had opportunity to be with the patients without another worker present. Finally, it is important to note that in this case before us, due to T.S.’s impaired mental facility, there could not be any direct testimony from her regarding who assaulted her.

Three justices (of seven) dissented in Hartman. Justice Steinmertz commented in his dissent on the presumption of innocence issue. “The 50 percent prior chance assumption does not require shifting the burden of proof to the defendant and is not an impermissible assumption; rather, it is part of a scientific theory and the jury should be so told.” Id. at 327. He noted that the assumption was not made in a vacuum, but was admitted only after evidence serving as the basis for the statistic was already admitted. Id. The probability of paternity statistic, Justice Steinmertz reasoned, is truly neutral. It equally assumes the defendant is not the putative father, no matter how damning the evidence in the case. Id. at 328.

We agree with Justice Steinmertz’s evaluation of the statistic. In the case before us, there was evidence that appellant had access and opportunity to have intercourse with T.S. The DNA test itself indicated appellant was the father of the child. Dr. Eisenberg testified in no uncertain terms that the theory was used as the standard method of reporting paternity tests. On cross, he testified about the effect of lower prior probabilities on the probability of paternity. As with any other expert testimony, the jury was free to disregard it entirely. Nothing about the statistic shifts the burden of persuasion to the defendant.

In contrast to Hartman, Skipper represents the strongest denunciation by a court of the probability of paternity statistic as violating the presumption of innocence. 228 Conn. 610, 637 A.2d 1101 (1994). There, the defendant was convicted of second degree sexual assault. The Connecticut Supreme Court stated “[t]he assumption that sexual intercourse had occurred was not predicated on the evidence in the case, but was simply an assumption made by the expert.” Id. at 1106. Since Bayes’ Theorem cannot be invoked without assuming a prior probability of paternity, the court reasoned that its use was inconsistent with the presumption of innocence. Id, at 1107. The Connecticut Court further reasoned that if a value presuming innocence was entered into the equation, the value being zero, then Bayes’ Theorem would produce a 0% probability of paternity. Id. at 1108. Beyond the fact that this decision rests on Peterson’s questionable conclusion, we simply do not agree with the Connecticut Court’s rationale.

In this instance, five individuals were determined to have access to T.S. during the period the child was conceived. Initially, there was no presumption assigned to any of these men’s paternity. Only after the men •with access were tested, and all but one excluded, was a prior probability employed. At that point, appellant was the only actual man included, and the statistic presumes either he or a random man could have been the father. Thus, the .5 prior probability accurately represents that he either is or is not the father.

Moreover, the presumption of innocence cannot require us to enter a prior probability of zero into Bayes’ Theorem as suggested by the Connecticut Court. A zero prior probability does not simply presume a defendant is innocent. Rather, a zero probability, in fact presumes that it was impossible for the defendant to be the father. When a zero prior probability is plugged into Bayes’ Theorem (the formula), naturally the probability of paternity results becomes 0%. The presumption of innocence does not require a jury to assume it was impossible for a defendant to commit the crime charged. Rather, it requires the jury to assume as a starting proposition that the defendant did not commit the crime, until proven otherwise. The probability of paternity, as Dr. Eisenberg testified, is merely a way of expressing and interpreting the actual DNA test results. Thus, the statistic itself does nothing to shift the burden of going ahead to the defendant.

Finally, appellant cites a third case, State v. Spann, 130 N.J. 484, 617 A.2d 247 (1993). There the New Jersey Supreme Court held that where the clear impression was given to the jury that the 50% prior probability was a scientific assumption, the admission of the probability of paternity statistic was reversible error. Id. at 253. In Spann, there was no explanation to the jury about how the evidence in the case might affect the prior probability, and how that would in ton affect the probability of paternity statistic. The court reasoned that a jury should use its own estimate of the prior probability of paternity, and not rely on the expert’s assumption of the defendant’s access to the woman. Id. at 254.

We note that the New Jersey Court did not conclude that the probability of paternity statistic violated the presumption of innocence. In fact, the court discussed a number of issues to help guide attorneys and courts in deciding whether the statistic would be admissible in any given case. Id. at 257-60. The court referred to concepts of general acceptance, reliability, and usefulness for the jury. Id. at 258. Ultimately, for future cases, the New Jersey Court left the determination of admissibility of the probability of paternity statistic to the trial court, implying that they found no interference with the presumption of innocence. Moreover, the Spann Court expressly rejected the suggestion that the Wisconsin Supreme Court arrived at in M.J.B., i.e., that intercourse must be proven before the probability of paternity statistic can be admitted. Id. at 261. The New Jersey Supreme Court stated that “[t]he calculation — Bayes’ Theorem — if valid, does not depend on any particular degree of confidence in the fact of intercourse.” Id.

The presumption of innocence places the burden on the State to move forward and prove that the defendant committed all the elements of the crime beyond a reasonable doubt. In a sexual assault case, one element the State must show is that the defendant caused “the penetration of the ... female sexual organ ...” of the victim. Tex. Penal Code Ann. § 22.011(a)(l)(A)(Vemon Supp. 1998). While it is true that the probability of paternity statistic presumes that the defendant could have had intercourse with the mother of the child, it does not assume that he did have intercourse. As Dr. Eisenberg testified, a prior probability of .5 assumes that the defendant is just as not likely the father of the child as it assumes he is the father. Moreover, even if the prior probability was .9, strongly presuming that he was the father, it still does not conclusively establish, or presume or assume he had intercourse with the woman. This is a matter for the jury based on all the evidence in the ease, which could include no access, impotence, vasectomy and other similar matters.

The Indiana Court of Appeals, over an objection that Bayes’ Theorem violated the presumption of innocence, expressly concluded that the probability of paternity statistic was admissible in a criminal trial. In Davis v. State, 476 N.E.2d 127 (Ind.App.1985), a husband and wife were convicted of neglect of a dependant. Their baby was abandoned on the side of a gravel road within hours of its birth. Using HLA testing and Bayes’ Theorem, the State showed that the Davis’s were the parents of the abandoned child. On appeal, the parents contended that Bayes’ Theorem violated the presumption of innocence.

In Davis, one element the State had to prove was that the abandoned child belonged to the defendants. Using parentage tests, the State was able to link the defendants to the child in order to prove that they had committed the crime charged. In the case before us, the State has also used parentage tests to link the defendant with the crime charged. The issue in Davis was whether Bayes’ Theorem could be used in a criminal case to show parentage. The Indiana appellate court determined that the .5 probability invoked in Bayes’ Theorem was a neutral consideration and that the probability of parentage statistic was admissible. Id. at 138.

In this instance, we conclude that probability of parentage statistic is admissible under Kelly v. State, supra, and that its admissibility under Kelly does not violate the appellant’s presumption of innocence. Appellant’s-first point of error is overruled.

Appellant’s Second Point of Error

In the alternative to his first point of error, appellant claims in his second point that the trial court erred by admitting the probability of paternity statistic because there was no testimony regarding the mathematical applications of the test results of the probability of paternity testing using Bayes’ Theorem. Under the point, appellant, in essence claims that as a condition of admissibility, the State is required to call a mathematical expert to comment on the possible interpretations of the statistical evidence. We disagree. Rule 702 and Kelly make no such requirement for the admission of the scientific evidence in question.

To support his position, appellant points out that where Bayes’ Theorem has been permitted, some courts require certain precautionary conditions be met before allowing the evidence. Particularly, he points to State v. Spann, 617 A.2d at 264. While the New Jersey Supreme Court indicated that it might be necessary to have expert testimony from a geneticist and a mathematician in order to allow Bayes’ Theorem evidence at trial, we note that the court was reviewing admissibility of evidence under its own state standard. As we have previously discussed above, in Texas the admissibility of scientific evidence is governed by Rule 702 of the Texas Rules of Evidence and the standard laid out in Kelly. Again, we are convinced that the statistical evidence presented in this case satisfied that test.

The record contains testimony from Dr. Eisenberg addressing the relevance and reliability of the probability of paternity statistic. In the hearing on the motion to suppress, he testified about his extensive credentials and expertise in the field of molecular biology as applied to genetic testing. He testified that the methodologies employed in the DNA testing were standard, including the statistical calculations that were used to interpret the test results. Specifically, he testified that use of the .5 prior probability was standard in parentage testing, and that it was a neutral factor since it did not “give any weight to either side” on the issue of paternity. Dr. Eisen-berg testified before the jury that if the prior probability in the calculation were reduced to .01(1%), reflecting a very low assumption that appellant was the father, the probability of paternity was still “in excess of 99 percent.” Finally, he testified that the tests run in this case were run twice in order to verify the results and rule out the possibility of errors. In light of this testimony, the trial court was within its discretion to admit the probability of paternity statistic under the Kelly test.

Even assuming arguendo that the probability of paternity statistic was improperly admitted, we conclude that such error was harmless. The defense had the opportunity to cross examine Dr. Eisenberg on the use of the prior probability. By cross, the defense pointed out to the jury the nature of the probability of paternity statistic and how it could be misleading. The defense did not question the other two statistics at all. Based on other evidence that appellant had access to T.S., that he had opportunity to be alone with her, that he knew she could not consent to sexual intercourse, that appellant matched on all six regions of DNA loci tested, that the test included him while excluding 99.99% of the male population of his race, and that his paternity index made him nearly 15,000 times more likely than the random man to be the father of T.S.’s child, we conclude beyond a reasonable doubt that the admission of the probability of paternity, even if error, made no contribution to the conviction. Appellant’s second point of error is overruled.

Appellant’s Third Point of Error

In his third point of error, appellant claims the trial court erred by overruling his motion to set aside the verdict and judgment rendered against him and grant him a new trial because the prosecution knowingly introduced inadmissible evidence clearly calculated to inflame the minds of the jurors against him. We disagree.

The complained of statements came from Janice Robinson, another state school employee. The State’s attorney asked Robinson if she was aware of a statement made by the appellant that the female clients of the State School were “easy” or that they “wanted sex.” Robinson answered the question affirmatively before defense counsel objected. Upon objection, the court held a hearing outside the presence of the jury. The court denied the defense’s motion for mistrial based on prosecutorial misconduct, then sustained the objection. The jury was brought back in, and the court ordered the jury to disregard the question and the answer. In essence, appellant contends that in offering the statement, the prosecution committed prosecutorial misconduct which constitutes reversible error. Again, we reiterate our disagreement.

The decision to grant or deny a motion for new trial is within the discretion of the trial court, and appellate courts will not reverse such decisions absent an abuse of discretion. State v. Gonzalez, 855 S.W.2d 692, 696 (Tex.Cr.App.1993). Moreover, error in asking an improper question or admitting improper testimony may generally be cured by an instruction to disregard. Livingston v. State, 739 S.W.2d 311, 335 (Tex.Cr.App.1987). An exception to this rule exists where it appears that the question or answer is clearly calculated to inflame the minds of the jurors and is of such a character as to suggest the impossibility of withdrawing the impression produced on their minds. Kemp v. State, 846 S.W.2d 289, 308 (Tex.Cr.App.1992). The issue is whether the jury was so affected by the question that they were unable to disregard it as instructed. Huffman v. State, 746 S.W.2d 212, 218 (Tex.Cr.App.1988).

Even if we concluded the question was calculated to inflame the minds of the jury, we cannot conclude that the question or answer was of such a character as to suggest the impossibility of withdrawing the impression produced on the jurors’ minds. At worst, the question placed before the jury the idea that the appellant may have made some statement indicating he thought the female clients at the state school were seductive or sexually aggressive. There was nothing in the offered statement indicating appellant actually had sexual intercourse with the female clients. The question and answer did not suggest that appellant had confessed guilt where the appellant was denying guilt at trial. See Ladd v. State, 629 S.W.2d 139 (Tex.App. — Dallas 1982, pet. ref'd).

Assuming without deciding that the evidence offered was inadmissible, we conclude beyond a reasonable doubt that any error was cured and otherwise rendered harmless by the trial court’s instruction to disregard. The trial court did not err in overruling appellant’s motion for new trial. Accordingly, we overrule appellant’s third point of error.

In conclusion, we overrule appellant’s three points of error and affirm the judgment of the trial court.

QUINN, J., concurring.

QUINN, Justice,

concurring.

I concur in the resolution of point one but for reasons different than the majority. The evidence obtained from the use of Bayes’ Theorem may be acceptably scientific and satisfy one prong of the Kelly test described by the majority. However, for the reason described below, I believe it to be too misleading and confusing to satisfy the second prong. Therefore, it was inadmissible. Nevertheless, the error was harmless given the rather undisputed and conclusive DNA evidence establishing that appellant fathered the child.

One is presumed innocent of a crime until proven guilty beyond a reasonable doubt. Tex.Pen.Code Ann. § 2.01 (Vernon 1994); Tex.Code Crim. Proc. Ann. art. 38.08 (Vernon Supp.1998); Homan v. State, 662 S.W.2d 372, 374 (Tex.Crim.App.1984) (en bane); Delo v. Lashley, 507 U.S. 272, 278, 113 S.Ct. 1222, 122 L.Ed.2d 620, 628 (1993). Admittedly, the standard actually speaks of the State’s burden of proof. But, it implicitly connotes that the fact finder must begin the journey of determining guilt with the belief that the accused did not do the criminal act until the State proves he did.

For instance, one can picture a child stacking ten blocks on top of each other. Before he can reach the pinnacle with the tenth block, the other nine must first be placed in order. So, the child starts with the first, then second, then third, fourth, fifth, sixth, seventh, eighth, and ninth. Eventually, the tenth is set atop the stack and his task is complete. The burden of proof imposed upon the State is analogous to stacking blocks, for the prosecutor is obligated to set bits of evidence, like blocks, atop each other to reach the level of proof mandated by law. And, before it can place the last block on the stack to achieve proof beyond a reasonable doubt, the other nine must first rest under it. He cannot simply ask the fact finder to presume that one or more of the nine are there. Rather, they must actually be there. And, therein lies the problem with using Bayes’ Theorem. For the theorem to have any meaning, the State is implietly asking the fact finder to presume that one or more of the blocks exist. That this is so can be seen from the application of the theorem to the circumstances at bar.

Here, the State was trying to prove that the appellant sexually assaulted the victim by having intercourse with her. One way to prove that he had intercourse was to prove that he was the infant’s father. Indeed, if he was the father then it would be quite reasonable to deduce that he had intercourse with the mother. Here, proving fatherhood was done by sampling the blood of the appellant, the victim, and the child. Once the blood was taken from each, it was then compared to determine the existence of common genetic markers. After that, the State endeavored to determine the number of men needed in a randomly selected pool for one of those men to have the same markers found in the comparison. That number constituted the paternity index, which here was 14,961. The index alone, however, did not illustrate that the accused was the father, but rather that a certain number of randomly selected men were needed in the pool to find one with the same genetic markers. What allegedly illustrated fatherhood was the application of Bayes’ Theorem to the index, for that resulted in the probability (or percentage chance) of paternity.

So, to find the relevant probability under the theorem, the paternity index was multiplied by an assumed percentage chance that appellant was the father. The assumed chance used here was 50% because that was purportedly neutral, ie., a 50% chance that he was the father and a 50% chance that he was not. This resulted in a product of 14,-961 (14,961 x 50/50 = 14,961). One (1) was then added to the product for a sum of 14,962. That sum was then divided into 14,-961 to derive the percentage chance that the accused is the father, and the percentage chance derived here equaled 99.99%. According to the supposed evidence obtained through the use of Bayes’ Theorem, there was a 99.99% chance that appellant fathered the infant, which for all practical purposes also meant that there was a 99.99% chance that appellant had intercourse with the mother.

As can be seen, for the State to convert its DNA testing into a statistic, it used a formula (Bayes’ Theorem) containing an element mandating the presumption that appellant had intercourse with the victim. And, most ironically, the particular act which was presumed to have occurred just happened to be the same criminal act not only which he was accused of committing, but also which the State was obligated to prove through actual evidence. So, in plugging Bayes’ Theorem into my building block example, what the equation does is ask the fact finder to assume that one or more blocks necessary to prove guilt already exists when the State has yet to prove their existence. And, in my view, that is inimical to the presumption of innocence (or burden of proof imposed on the State) and renders the theorem and its statistical result highly misleading.

As to Dr. Eisenberg’s statement that the use of a .5 factor is neutral, I find the comment misleading when applied in the setting of a criminal trial. In the realm of statistics, a 50/50 chance is neutral; that is, it accurately depicts the notion that something is as likely as not to occur. Yet, to' be innocent, according to Black’s Law Dictionary, means to be free of guilt or guiltless. That means, in the common parlance of a layman, that the accused did not do the act. So, to presume one innocent is to presume that he did not do the act; it is not to presume that there is a chance he did the act. If the presumption were to be assigned a location on the .00 to 1.00 statistical scale used by Eisenberg, it would have to lie at .00. This is so because only there can it be said with certainty that he did not do the act. Placing it elsewhere on the scale would suggest, however slight, that he did. Because locating the starting point at .00 would render Bayes’ Theorem ineffective illustrates to me why it had no place in the trial to begin with.

I cannot deny the value of math in our day, time, and profession. Yet, while statistics and mathematical principles may facilitate resolution of legal questions, they cannot supplant criminal jurisprudence. Two plus two will always equal four, for that is an arithmetic principle. But, before two plus two can equal guilt, an immutable principle of criminal justice mandates that the State prove two and two exist in the first place. That is part and parcel of the presumption of innocence. And, all attempt to circumvent that principle must be avoided.

Nevertheless, I must also acknowledge the value of science and heed its teachings. The science here pivotal was that of DNA extraction and comparison. The evidence of extraction and comparison proffered by Dr. Eisenberg (sans conversion into statistic) established that the child could have obtained her DNA only from her mother and appellant or appellant’s identical twin. Moreover, while appellant did little to contest that DNA evidence, he utterly negated any possibility that his identical twin could have been the father by admitting he had no twin. Given these circumstances and this evidence, I must conclude that any error in admitting the results garnered via Bayes’ Theorem was harmless. 
      
      . "Although relevant, evidence may be excluded if its probative value is substantially outweighed by the danger of unfair prejudice, confusion of the issues, or misleading the jury, or by considerations of undue delay, or needless presentation of cumulative evidence.” Tex.R. Evid. 403.
     
      
      . Although parentage testing based on DNA analysis has only been on the scene since the mid to late 1980’s, a number of methods, including Human Leukocyte Antigen (HLA) tests, have been previously employed in paternity matters. HLA testing invokes the same statistical calculations, including the probability of paternity and Bayes Theorem. Dr. Eisenberg testified that in the past several years, nearly a million paternity tests in the U.S. were conducted using DNA or HLA methods, each using the .5 prior probability calculation.
     
      
      . Ultimately, there was testimony before the jury that the use of a .01(1%) prior probability would still generate a probability of paternity of over 99.3% in this case.
     
      
      . In Lagrone v. State, 942 S.W.2d 602, 608 (Tex.Cr.App.1997), the Court of Criminal Appeals mentioned Dr. Eisenberg's opinion on the probability of paternity statistic without passing on the issue before us. We note that the probability of paternity statistic has been admitted in a number of jurisdictions in criminal trials prior to this case. However, in those cases, the statistic was not challenged as violating the presumption of innocence. See State v. Foster, 949 S.W.2d 215, 217 (Mo.App. E.D.1997); State v. Pierre, 606 So.2d 816, 817-20 (La.App. 3 Cir.1992); People v. Taylor, 185 Mich.App. 1, 460 N.W.2d 582, 585 (1990); Martinez v. State, 549 So.2d 694, 696-97 (Fla.App. 5 Dist.1989); Holley v. State, 523 So.2d 688, 689 (Fla.App. 1 Dist.1988); State v. Smith, 735 S.W.2d 831, 833-35 (Tenn.Cr.App.1987); State v. Thompson, 503 A.2d 689, 690-93 (Me. 1986); Bridgeman v. Commonwealth, 3 Va.App. 523, 351 S.E.2d 598, 602-03 (1986); People v. Alzoubi, 133 III.App.3d 806, 89 Ill.Dec. 202, 479 N.E.2d 1208, 1209 (3 Dist.1985).
     
      
      . We note that M.J.B. is a civil paternity case. The Wisconsin Court allowed the probability of paternity statistic primarily due to a state statute allowing such evidence in civil paternity cases. Nevertheless, the Hartman decision seems to depart from the rationale in MJ.B. while relying on some of that case’s language.
     
      
      . Likewise, a prior probability of 1 (or 100%) would assume that no one else but the accused could have been the father.
     
      
      . This case involved Human Leukocyte Antigen (HLA) testing rather than DNA testing, but Bayes’ Theorem is used to calculate probability of paternity in both tests.
     
      
      . At the time of trial, the Texas Rules of Criminal Evidence and Texas Rules of Civil Evidence were still separate. As of March 1, 1998, these rules have been consolidated. While the new rules technically do not apply to this matter, we note that the current Rule 702 is identical to the old Rule 702 under the Criminal Rules.
     
      
      . Although we conclude that the statistical evidence was properly admitted, it is worth noting that the statistics merely reinforce the truly damning evidence in this case — the DNA test itself. Eisenberg testified that only the biological father or his identical twin would match the child's DNA at every site tested. Appellant himself testified that he did not have an identical twin. Eisenberg stated that based on the DNA test, it was his- opinion that appellant was the father of the child, barring a first order relative (i.e. brothers or father) or an identical twin. As between first order relatives, appellant was 64 times more likely to be the father. Here, the test results speak for themselves. Appellant matched at all six genetic sites tested.
     
      
      . Appellant waived his right to remain silent, and took the stand voluntarily. On cross, he conceded that there was a "possibility” that he had time alone with T.S., he knew T.S. was "very retarded” and she "probably” couldn't understand the nature of sexual contact or activity, and that he could not explain why the DNA test results came out as they did.
     
      
      . This is not to say that fatherhood indisputably proves intercourse, however. As a result of modern science, a female may become pregnant without ever having intercourse with anyone.
     
      
      . According to the testimony, the assumed chance can be most any that one wants to input, such as 50% as here, or 25%, 10%, or 1%, but it has to be more than 0%. If it were zero then the product derived from multiplying the percentage chance by the paternity index would be zero. In other words, the use of zero would result in a finding of no chance of paternity.
     
      
      .14,961 / (14,961 + 1) = 99.99.