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The Impact of Daubert v. Merrell Dow Pharmaceuticals, Inc., on Expert Testimony With Applications to

Business Law

When the U. S. Supreme Court handed down its opinion in Daubert v. Merrell Dow Pharmaceuticals, Inc., 125 L. Ed. 2d 469 (1993), it began a wide-ranging debate about the rules that govern the admissibility of expert testimony in both state and federal trials. The courts of 19 states have adopted Daubert, and those of 11 states, including Florida, apparently have rejected it.1 Over 100 articles have been published in response to the decision,2 and there are several Daubert websites, including one sponsored by Harvard Law School. This vigorous response is not surprising, because Daubert held that the Federal Rules of Evidence had displaced the 50-year-old Frye “generally accepted” standard for the admissibility of scientific testimony in federal trials and then determined a new “standard for admitting expert scientific testimony in a federal trial.” Daubert, 125 L. Ed. 2d at 476. Despite substantial disagreement in the legal community about what Daubert really means, this article’s perspectives are that the meaning of the Court’s scientific dialogue is fairly clear and that even though the scientific principles that the Court articulates are ultimately discussed as scientific and statistical concepts that are somewhat alien to the legal system, the Court’s holding has its basis in principles of philosophy and logic that have long informed the law.

The philosophy of science that the Court draws so heavily upon focuses on the nature of scientific investigation and informs virtually all of modern scientific inquiry, from DNA testing (do the blood samples match?), through medicine (does smoking cause lung cancer?), epidemiology (does Bendectin cause birth defects in human embryos?), economics (does spending rise with income?), and finance (did the release of fraudulent information cause the firm’s stock to rise?). The philosophy of science provides the framework that practitioners in all of these disciplines use to analyze data to find out whether their theories (smoking causes cancer; the release of fraudulent information caused the stock’s price to rise) are correct, and once one understands the philosophical basis of science upon which the Court relies, much of the statistical part of scientific testimony just plain makes sense and that is half, and perhaps more, of understanding the entirety of the expert testimony that is offered in courts today.

This article begins by outlining the Court’s holding and discussing the scientific framework that is the basis of the Court’s analysis. Included in this discussion of the scientific framework employed by the Court is a discussion of how the fundamental statistical concepts that experts use in their testimony have evolved from the scientific framework that the Court articulates. Most of the article’s statistical analysis of existing cases is from disciplines like epidemiology and DNA testing, since those are the areas that have most notably made their way into the legal system. However, the article also draws parallels from the techniques used by epidemiologists and DNA analysts to analogous techniques used in other fields, especially finance and economics. Demonstrating the similarity of the scientific techniques employed in these branches of science supports the article’s contention that once one becomes conversant in the scientific techniques used in any one of these disciplines, that knowledge goes a long way toward understanding the scientific techniques used in the others. The article concludes with a discussion of the role of Daubert in Florida courts, which seems to be somewhat more extensive than what some Florida courts believe it to be.

The Daubert Court begins its explanation of the criteria that trial courts should use to screen “purportedly scientific evidence” by parsing Rule 702, focusing on the meanings of “scientific” and “knowledge.”3 An important key to understanding the Court’s reliability-based analysis of the admissibility of expert testimony lies in the Court’s focus on the requirement that, in order for expert testimony to be admissible, “[t]he subject of an expert’s testimony must be ‘scientific. . . knowledge,’” because it is “the requirement that an expert’s testimony pertain to ‘scientific knowledge’” that “ establishes a standard of evidentiary reliability ” (emphasis added). Daubert, 125 L. Ed. 2d at 480–81. But, “in order to qualify as ‘scientific knowledge,’ an inference or assertion must be derived by the scientific method. . . . ” Id. In brief, since only scientific knowledge can be offered as scientific expert testimony, and the Court regards as scientific knowledge only that which is derived by the scientific method, only inferences that are derived by the scientific method can be offered as expert testimony.

The Court repeatedly uses the phrase “the scientific method.” This is a term of art with a specific meaning in the scientific community, and the Court’s discussion of the scientific method quotes from seminal works on scientific inquiry more than enough to make it clear that the Court is using the term in that manner. Indeed, much of the language relied upon by the Court in its discussion of the scientific method is strikingly similar to the language used in several amicus briefs filed by or on behalf of scientists from industry and academia.4 The Court stated that:

Ordinarily, a key question to be answered in determining whether a theory or technique is scientific knowledge that will assist the trier of fact will be whether it can be (and has been) tested. “ Scientific methodology today is based on generating hypotheses and testing them to see if they can be falsified; indeed, this methodology is what distinguishes science from other fields of human inquiry.5

Daubert, 125 L. Ed. 2dat 483 (emphasis added).
The testing of hypotheses that the Court’s emphasized language requires is called “hypothesis testing” and as the Court’s quotations indicate, hypothesis testing is the essence of the scientific method. It is noteworthy that the Daubert Court required that experts follow this “scientific method” even before it turned to the four factors that commentators and lower courts have fixed upon. This is noteworthy because the scientific method is the cornerstone of the philosophy of science and because testimony that conforms to the scientific method will always satisfy the Court’s first two criteria. The four Daubert criteria for evaluating the admissibility of expert testimony are: 1) whether the methods upon which the testimony is based are centered upon a testable hypothesis; 2) the known or potential rate of error associated with the method; 3) whether the method has been subject to peer review; and 4) whether the method is generally accepted in the relevant scientific community.6 Given the rest of the opinion, it seems appropriate that the first two of the Court’s four criteria amount to asking whether the techniques upon which the testimony is based are grounded in the scientific method. It is no less appropriate that virtually no expert testimony will satisfy the last two factors unless it satisfies the first two.

The Scientific Method and Daubert’s Four Factors

• Hypothesis testing. Hypothesis testing is the process of deriving some proposition (or hypothesis) about an observable group of events from accepted scientific principles, and then investigating whether, upon observation of data regarding that group of events, the hypothesis seems true.7 Because it is hypothesis testing that distinguishes the scientific method of inquiry from nonscientific methods, and because the scientific method of inquiry is required for the resulting inferences to be the basis of admissible expert testimony, hypothesis testing would be deserving of careful consideration even if it were not one of the Court’s four enumerated factors. The basic technique of hypothesis testing has been well settled for decades and an example demonstrates the technique.

A simple example of hypothesis testing: Looking at a single six-sided die might lead one to the proposition (or hypothesis) that each of the six numbers is equally likely to be rolled on each roll of the die. This hypothesis is tested scientifically by proposing the “null hypothesis”8 that each number is equally likely to land face up, and then rolling the die (say) 600 times and recording the number of times that each number is actually found face up. If an appropriate statistical test is used, and if each number occurred about 100 times, the statistical test will be unable to reject the null hypothesis of equal probabilities, and the scientist will be left with the likelihood that the die is fair. However, if the number “3” occurs a disproportionate number of times, say 200 times out of 600 rolls, then the statistical test will be likely to reject the null hypothesis of equal probabilities and the scientist will interpret this as evidence that the die is loaded and reject the null hypothesis.

The known or potential error rate. The second parameter that Daubert suggests that trial judges use in evaluating the scientific validity and, therefore, evidentiary reliability of “proported scientific testimony” is the “known or potential rate of error,” Daubert, 125 L. Ed. 2d at 469, associated with using the particular scientific technique. In plain language, this is the likelihood of being wrong that the scientist associates with the assertion that an alleged cause has a particular effect. Most scientists routinely require that this error rate be very small, usually between one and five percent.

There are two types of error rates in testing hypotheses and they are denoted as “Type I Error” and “Type II Error.” In layperson’s terms, a Type I Error is a false positive and a Type II Error is a false negative. For example, if a drug test for a substance comes back positive, but the tested individual has not actually used the drug, a layperson would call that a false positive, while a scientist would call it a Type I Error.9 A test’s propensity for this Type I Error is the most commonly cited component of the “error rate” in hypothesis testing. This error rate is also known both as the “level of confidence” of the hypothesis test and as the level of statistical significance of the test’s result. A common assertion in scientific research is that “the null hypothesis is rejected at the 1 percent level,” or equivalently “the result is statistically significant at the 1 percent level,” which means that the statistical technique used to test the hypothesis, if applied to data where the null hypothesis is true, would reject the null hypothesis only one percent of the time. If such a statement were made about the example of the single die above, it would mean that if the die were not loaded and the experiment of rolling it 600 times and testing the null hypothesis that the die was fair were done 100 times, 99 of those tests would correctly show the die to be fair, while one of those tests would incorrectly show the die to be loaded.

• Peer review and publication. The third criteria that the Supreme Court suggested for use by trial courts in determining whether expert testimony reaches the trier of fact is “whether the theory or technique has been subjected to peer review and publication.” Publication typically is the purpose for which research is offered up for peer review and passing the peer review is required for publication. “Peer review and publication” of a scientist’s work is largely a term of art that means that the scientist’s peers have sanctioned the work as credible and accepted it for publication. Publication then exposes the work to further review by other scientists whose responses to the research indicate their agreement or disagreement with the methods and results of the work. Properly executed hypothesis tests with their attendant error rates are the essence of scientific method and are very nearly necessary conditions for peer review to result in publication.

• General acceptance. Like the Court’s third criterion, this is a summary measure of the extent to which the expert’s methods produce information that qualifies as scientific knowledge. Scientific methods begin the process of becoming generally accepted in the scientific community by bringing appropriate hypothesis testing techniques to bear on questions (or hypotheses) of interest to the scientific community in a fashion that results in the peer approval required for publication. They move toward general acceptance by then withstanding the scrutiny of the broader scientific community to which publication exposes the methods.

It is interesting to note that a scientist reading Frye and Daubert might say that Daubert explains Frye almost as much as it displaces it. Frye defined the evidentiary issue as reliability and then deferred fully to an amorphously defined “scientific community” for its “general acceptance” which it used as a proxy for evidentiary reliability. Daubert still looks to the scientific community for its general acceptance as an indicator of evidentiary reliability, but it also recognizes that there is a basic structure of inquiry known as the scientific method that is the standard used across different branches of science for their scientific investigations, and it requires that the science proffered to the federal bench be grounded in that basic structure. This requires posing and testing hypotheses and specifying the rates of error for those hypothesis tests. Daubert first specified these criteria indirectly by requiring that expert testimony adhere to the scientific method, and then subsequently posed them explicitly as the first two of its four Daubert factors. Finally the Court specified them indirectly again when it posed general acceptance and publication in peer-reviewed journals as criteria for admissibility of expert testimony, because peer review, publication, and general acceptance require hypothesis testing and error rates. In this light it is interesting to note that while the Court introduced its list of four factors as not being a definitive list, testimony that is not based upon a test of a hypothesis will tend to fail all four of the Court’s criteria and tend strongly toward inadmissibility.

An Example from
Securities Litigation

Current events provide an example of how the principles that underlie Daubert are applied in a securities litigation context. A large Florida corporation has recently been in the news because of allegations that the company’s financial statements reported exaggerated sales figures. Following the release of this information, the corporation’s stock fell sharply and several pending lawsuits allege that a class of the corporation’s stockholders has been damaged by purchasing stock whose price was inflated by the alleged overstatements. If this litigation proceeds, economists will estimate the damages that were alleged to have been suffered by this class of stockholders.

Economists have a generally accepted technique for measuring the impact of the release of new information on the price of a publicly traded security. This technique, called an event study, has been the basis of hundreds of articles that have been published in peer reviewed journals.

Economists believe that the current value of a security is equal to the present value of all of the payments that the security will make to its owners throughout its life, and that the value of a security changes when new information is released into the market that changes the market’s assessment of the future payments that the security will make to its holder. When information comes into the market that is hypothesized to affect the value of a particular stock, economists test that hypothesis by comparing how that particular stock performed right after the release of the information to how the stock would have been expected to have performed in the absence of the release of the new information.

The event study technique ascribes this change in the stock’s performance or value to the event that the information disclosed. In the case of the Florida corporation mentioned here, this information is the release of allegations that its reported sales figures were inflated. The event study is the financial economist’s standard technique for determining the impact of mergers, dividend and earnings announcements, management changes, and a host of other phenomena upon the value of the subject firm’s stock, so it has well-established nonlitigation uses. The heart of the technique is a test of the null hypothesis that the information had no impact upon the price of the stock. The economist will reject this null hypothesis if and only if the hypothesis test yields both an estimate of the change in the stock’s value that is non-zero, and an error rate of the test that convinces the economist that sampling error has not caused the non-zero estimate of the change in the stock’s value. This technique meets all of the Daubert criteria: It poses and tests a hypothesis, reports the pertinent error rates, and is based upon peer reviewed and published techniques that are so pervasively used within the relevant scientific community that they are the generally accepted tool for evaluating the impact of the release of new information upon the value of a publicly traded security.10

It is difficult to overstate the importance of excluding improper money-damages testimony. Where jurors lack the capacity to evaluate the scientific merits of either party’s expert’s testimony, it takes little effort to imagine a jury simply rough-averaging the money damage numbers put forth by the opposing experts. “This guy says $600 million, that guy says $40 million. I can’t tell which one is right, but they both seem nice, so let’s go somewhere in the middle, say $300 million.” If the $600 million estimate could have been excluded by a motion in limine, defendant could have saved $240 million. Since the motion and its supporting analysis may require around 100 hours of attorney/expert time, its cost/benefit analysis is too compelling to ignore. The expected internal rate of return on the expenses required to prepare the motion can easily exceed 1000 percent. This is a notion to which counsel’s corporate clients will relate particularly well, and it continues to be true when the stakes are $6 million instead of $600 million and the motion has only one chance in 10 of succeeding. The analysis is the same for plaintiff’s attempts to exclude the testimony of defendant’s expert. Finally, such a motion is very powerful for purposes of settlement negotiations because redefining what the jury will hear can redefine the range of settlement discussion.

A Few Notes on
the Florida Frye Test

In Brim v. State, 695 So. 2d 268, 271 (Fla. 1997), the Florida Supreme Court rejected Daubert, writing that “despite the federal adoption of a more lenient standard in Daubert. . . we have maintained the higher standard of reliability as dictated by Frye.”11 However, in rejecting Daubert, the court seems to move in the direction of construing Frye, itself a reliability driven test, into a sort of virtual Dauberthood.

Florida’s Frye test relies on general acceptance as a proxy for evidentiary reliability12 and publication in peer-reviewed journals13 as an indication of that general acceptance. But, as noted earlier, publication is part of the process by which a scientific technique becomes generally accepted and such publication in scientific journals is very rare unless the study’s conclusions are derived by posing hypotheses and testing them at given levels of statistical significance. In short, when Florida courts require that the expert’s methods be accorded general acceptance and perhaps publications in peer-reviewed journals as evidence of that acceptance, they seem implicitly to require that the expert’s methods be based upon hypothesis testing and the error rates of those tests.

Analyzing Brim’s Frye-test logic seems to confirm the existence of this implicit requirement. The court observes that “the DNA testing process consists of two distinct steps,” that the first step relies on biology and chemistry, while “a second statistical step is needed to give significance to a match,” Brim, 695 So. 2d at 269, because “to say that two patterns match without any scientifically valid estimate of the frequency with which such matches might occur by chance is meaningless.”14 This “chance matching” is precisely the error rate of the test of the hypothesis that the DNA profiles match. Since the calculation of such an error rate requires that the hypothesis be tested, the de facto requirement posed here by the court is that the expert conduct the hypothesis test and report its error rate.

In its discussion of the need for the statistical step the court relies substantially on The Evaluation of Forensic DNA Evidence,15 published by the National Academy of Science and authored by a blue ribbon panel of scientists, professors, and lawyers. Chapter 5 of this volume describes the statistical techniques used in DNA research which involves posing hypotheses, testing them, and specifying their error rates. The chapter begins its discussion by suggesting that the scientist “evaluate the probability of finding”16 a false positive. Again, this probability of finding a false positive is the Type I Error, or to use its more familiar name, it is the level of statistical significance at which a hypothesis is tested. Of course, since finding the probability of rejecting a true hypothesis requires testing that hypothesis, this necessarily tells DNA analysts to test an appropriate hypothesis and report the results of the hypothesis test and its level of statistical significance, which is of course the probability of finding a false positive.17

Chapter 5 continues by discussing the notion of confidence intervals, which is the more intuitive but mathematically identical twin of the technique of testing a hypothesis at a given level of significance.18

Even though in Brim the Florida Supreme Court has declared its rejection of Daubert, the opinion cites with approval the scientific and statistical language of learned treatises that ultimately instruct the empirical scientist/expert witness to pose a hypothesis that is implied by generally accepted biology or chemistry and then instructs them to test that hypothesis, reporting the results of the test and the error rate associated with the test. In short, the sources that the Brim court cites tell experts to conform to Daubert’s first two criteria. Since Florida’s Frye test already rests on Daubert’s third and fourth criteria, it is becoming increasingly difficult to distinguish between testimony that will satisfy Daubert and testimony that will satisfy Florida’s Frye progeny. As long as Florida courts cite scientific propositions in learned works produced by scientists and scientifically sophisticated lawyers, they are going to be citing work that is couched in terms of the hypothesis tests and error rates that facilitate publication in peer-reviewed journals19 and these Daubert mandated techniques will continue to leak into the opinions of Florida courts, bringing in by the back door what the Florida Supreme Court has, so far, declined to admit by the front. q

1 David L. Faigman, David H. Kaye, Michael J. Saks and Joseph Sanders, Modern Scientific Evidence: The Law and Science of Expert Testimony §1-3.0 (1997).
2 Id.
3 Rule 702, “Testimony by Experts” reads: “If scientific, technical, or other specialized knowledge will assist the trier of fact to understand the evidence or to determine a fact in issue, a witness qualified as an expert by knowledge, skill, experience, training, or education, may testify thereto in the form of an opinion or otherwise.” The Court explained that “[t]he adjective ‘scientific’ implies a grounding in the methods and procedures of science. Similarly, the word ‘knowledge’ connotes more than subjective belief or speculation.” Daubert, 125 L. Ed. 2d at 480. Combining the implications of these two words, the court limited expert testimony on scientific issues to that which is “scientific knowledge,” produced by the scientific method.
4 There were 25 amicus briefs filed in Daubert and they are available on Lexis. The briefs filed by The Carnegie Commission on Science, Technology, and Government, filed in support of neither party, and by A Group of American Law Professors filed in support of neither party stand out as well reasoned articulations of the nature of scientific inquiry and the role of science in the legal system.
5 “Falsify” is an unfortunate choice of words here. The more common term is “reject,” and scientists routinely speak of ‘rejecting an hypothesis’ to indicate that analysis of the available data makes the hypothesis seem false.
6 It is important to note that the Court has not written anything in Daubert that would surprise scientists. The proposition that hypothesis testing is the essence of the scientific method and that the scientific method is the indispensable cornerstone of scientific investigation is about as widely questioned in the scientific community as the proposition that Learned Hand was an influential 20th century federal judge is questioned in the legal community. See Daubert, 125 L. Ed. 2d at 483 and the citations therein.
7 See Jan Kmenta, Elements of Econometrics 112–17 (1971). Scientists conduct such “observation” by applying appropriate statistical methods to appropriate data. This is what scientists call empirical research. Webster defines “empirical” as “capable of being verified or disproved by observation or experiment.”
8 In the basic model of hypothesis testing, scientists pose hypotheses in pairs. The hypothesis that is actually tested is called the null hypothesis, and it alleges that there is “no difference” between populations or “no effect” of some treatment or event. So a null hypothesis might say that there is no difference among the probabilities of a certain number coming up on the die, or that there is no effect of a merger announcement on the value of a firm’s common stock. The alternate hypothesis is that there is a difference in the die face probabilities or that the announcement of a merger does affect the price of the acquired firm’s stock. One tests the null hypothesis (often called just “the null”), and either rejects it at a certain level of confidence or fails to reject it. While there is no scientific means for accepting a null or alternate hypothesis, if one tests the null and fails to reject it one says that there is no effect or, speaking more carefully, that the attempt to reject the null failed. If one rejects the null hypothesis, one is left only with the alternate hypothesis, and, again, while no mechanism exists for accepting either hypothesis, a rejection of the null constitutes strong evidence that the alternate hypothesis is true. See Kmenta, supra note 7, at 112–16 (discussing hypothesis testing).
9 If the drug test comes back negative and the tested individual has used the drug, that is a “false negative,” a Type II Error.
10 It is interesting to compare this technique that is actually used by economists to a set of techniques that forensic economists refer to as damage ribbons and value lines. These techniques, which were routinely admitted in many federal courts prior to Daubert, are apparently no longer admissible because they seem to meet none of the Daubert criteria. One interesting aspect of the comparison is that virtually all of the computer programs that a forensic economist would use to calculate a damage ribbon would also calculate everything necessary to perform the hypothesis tests and error rates required by Daubert. See Bradford Cornell and R. Gregory Morgan, Using Finance Theory to Measure Damages in Fraud on the Market Cases, 37 UCLA L. Rev. 883, 899 (1990) (providing a thorough description of the techniques).
11 It seems less than clear that Daubert is a more lenient standard than Frye. Judge Jack Weinstein, author of the well known multi-volume evidence reference set, observed that judges are “going to have to give a more reasoned statement about why they are letting in evidence” and that “[t]hey can’t do it on a rubber stamp basis the way some of them did it in the past.” Rorie Sherman, “Junk Science” Rule Used Broadly, Nat’l L.J. 28 (Oct. 4, 1993). See also David L. Faigman, David H. Kaye, Michael J. Saks and Joseph Sanders, Modern Scientific Evidence: The Law and Science of Expert Testimony §1-3.3.4 (1997) (stating that “in those areas of science with a tradition of rigorous research, Daubert can be expected to be more liberal, but in those areas without such a tradition, it should be expected to be more conservative”).
12 Brim, 695 So. 2d at 272; Hadden v. State, 690 So. 2d 573, 578 (Fla. 1997); Ramirez v. State, 651 So. 2d 1164, 1167 (Fla. 1995).
13 See Berry v. CSX, 1998 Fla. App. Lexis 2243, *61 (noting that “peer-reviewed epidemiological studies conducted independently of the instant litigation are the scientifically accepted means of analy[sis]”); see also Williams v. State, 1998 Fla. App. Lexis 2706, *26 n.15 (noting with approval that proffered results had been subject to peer review), *57 n.42 (Cope, J., concurring in part and dissenting in part) (quoting that “[p]eer review and publication provide the opportunity for others in the field to examine and critique the reasoning or methodology behind scientific theory,” citing State v. O’Key, 321 Ore. 285; 899 P.2d 663, 679 (Ore. 1995)).
14 Brim, 695 So. 2d at 270. This conclusion is also supported by the court’s declaration that “the underlying principles used to calculate those statistics must be generally accepted in the relevant scientific community.” This passage alone apparently requires hypothesis testing at a given level of statistical significance, for if there are generally accepted statistical techniques that proceed without hypothesis tests the statistical community is keeping them well hidden.
15 Brim, 695 So. 2d at 270. The court cited to the “Prepublication Copy.” This article’s citations to the treatise are to the published copy, cited infra, note 16.
16 Committee on DNA Forensic Science: An Update, The Evaluation of Forensic DNA Evidence 127 (1996). The treatise’s actual statement reads, “We want to evaluate the probability of finding this profile in the ‘someone else’ case.” This is scientific parlance for finding a false positive—i.e., finding this DNA pattern in someone who is not the “suspect.”
17 The treatise offers an interesting alternative to this procedure, which is to “calculate the likelihood ratio (LR), a measure of the strength of the evidence regarding the hypothesis that the two [DNA] profiles came from the same source (the suspect).” The likelihood ratio is calculated for the purpose of conducting a likelihood ratio test of the hypothesis that the (say) blood samples found at the scene of the crime were left by the suspect. The likelihood ratio test is, by definition, conducted at a certain level of statistical significance, or error rate. This apparently is a popular statistical test. For an example from economics, see George Judge et al., The Theory and Practice of Econometrics 758 (stating that “The likelihood ratio test involves both constrained and unconstrained estimators. The null hypothesis is rejected if

7 = 2[ln l ( $ ML , F2 M L ) – ln l ( $ R , F2 R )]

exceeds P2 ( J , “) for a prespecified significance level “.”
18 Kmenta, supra note 7, at 189 (explaining the equivalence between the confidence interval and the hypothesis test). For example, if the die discussed above is fair, rolling it will result in a “3” 16.66 percent of the time, and one can reject the hypothesis that the die is fair (which is evidence that the die is not fair) at the 99 percent confidence level if and only if the confidence interval around the estimate of the die’s probability of showing “3” fails to contain 16.66 percent. For example, if the 99 percent confidence interval is (18.4 percent, 22.8 percent), then the scientist can take this as evidence that the die is loaded, because the 16.66 percent that a fair die would generate is not in the confidence interval. However, if the confidence interval is (14.4 percent, 18.3 percent) then the scientist can take this as evidence that the die is fair. The scientifically well-established equivalence of these two techniques has not kept courts from drawing some interesting distinctions between the two. See Berry, supra note 13, at *20 (relying upon the confidence interval technique after an informed discussion of the technique that cites highly informed sources, but then going on to discuss statistical significance with disapproval).
19 See David L. Faigman, David H. Kaye, Michael J. Saks and Joseph Sanders, Modern Scientific Evidence: The Law and Science of Expert Testimony 1-3.3.1 (stating that “in science, a non-testable hypothesis cannot have an error rate and is exceedingly unlikely to be published in a peer reviewed journal and achieve general acceptance.”). This volume, to which the Berry court cites repeatedly for scientific propositions, provides an extensive and articulate exposition of the principles of science.

Stephen Mahle received his Ph.D. in economics from The Ohio State University and his J.D. from the University of Virginia Law School, where he was Olin Fellow in law and economics. He is adjunct professor of law at the Nova Southeastern University Law School, has been a finance professor at several major universities, and practices law in Boca Raton. Dr. Mahle practices, writes, and teaches in the areas of finance, securities litigation, and expert testimony.
This column is submitted on behalf of the Business Law Section, Stephen D. Busey, chair, T.A. Borowski, Jr., editor, and Donald A. Workman, guest editor.

Business Law