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Statistician may testify in alleged profiling case

Where an officer sued for racial profiling moved to preclude a statistician from testifying that the likelihood of his higher rate of citations of Black drivers versus lower rates by other officers, by chance, is about 1 in 100,000, his motion was denied. The testimony was relevant and was based on sufficient data.


Plaintiffs have brought these consolidated cases alleging claims of selective enforcement of the laws and racial profiling primarily by defendant officer Holmes, in violation of the Equal Protection Clause of the Fourteenth Amendment. Defendants have filed a motion in limine seeking to exclude plaintiffs’ expert testimony from a statistician, who would testify that the likelihood of Holmes’ higher rate of citations of Black drivers versus lower rates by other officers, by chance, is about 1 in 100,000.


This court previously excluded the underlying statistics plaintiffs offered as insufficient to support the element of plaintiffs’ claim that they show Holmes’ conduct had a “discriminatory effect.” However, the Fourth Circuit reversed, concluding that defendants had provided no reason to justify excluding plaintiffs’ statistical evidence as a matter of law. Given the Fourth Circuit’s ruling, the court considers defendants’ relevancy arguments unpersuasive.

The standard for relevance is relatively low. Dr. Rovnyak providing testimony describing the statistics of Holmes’ number of citations to Black drivers and calculations that the number was higher to a statistically significant degree than others in his department is evidence that tends to make it at least somewhat more likely that Holmes acted with discriminatory intent and with a discriminatory effect. While the record on appeal was insufficient for the Fourth Circuit to conclude “whether the proffered statistics establish [plaintiffs’] claims as a matter of law,” the Fourth Circuit’s opinion demonstrates that they certainly are relevant to support plaintiffs’ claims.

Defendants raise a variation on this argument, that plaintiffs’ expert testimony should be excluded as “irrelevant” because it only concerns correlation, not causation. This argument fares no better. Although “selective enforcement and selective prosecution claims may be difficult to prove,” the Fourth Circuit explained that such claims “are not (and should not be) impossible to prove,” and the Fourth Circuit has further cautioned against “imposing a standard of proof that defies statistics.”

To be sure, defendants’ point is not wholly without force. “Correlation and causation are two different things.” But that does not mean evidence of a correlation is per se irrelevant. At bottom, defendants’ cited authority does not support their attempt to exclude plaintiffs’ expert’s testimony. Indeed, far from attempting to “masquerade” evidence of correlation as causal evidence, plaintiffs’ expert appears to candidly acknowledge the limitations of her statistical analysis in the portions of her deposition testimony cited by defendants. Nor is this a circumstance in which an expert has “failed to distinguish between ‘correlation’ and ‘causation.’”

Defendants also argue that plaintiffs’ expert’s “calculations are irrelevant” because she “considered no factors or information other than race.” This mirrors defendants’ argument to the Fourth Circuit that plaintiffs’ “statistics are insufficient because they are not detailed enough to exclude certain possible legitimate law enforcement factors that may explain the stark disparity in Holmes’s rate of traffic summonses for African American individuals.” And, notably, the Fourth Circuit rejected that argument.

Similarly, defendants’ argument that plaintiffs’ expert lacked sufficient data does not support excluding her opinion or calculations. This is another repackaged and repurposed argument that the Fourth Circuit already largely rejected. And while defendants cite their own expert, saying that because the sample size of comparator- officers to Holmes was small, “caution must be exercised,” and that having “more data” results in more accuracy, that is fair. Caution must be exercised. The more data the better. But neither principle warrants exclusion of the testimony and calculations on this record.

Lastly, this court also considers the Fourth Circuit’s admonition that plaintiffs have been forced to rely on defendants for the statistical information to prove their claim, which is here (as on appeal), being challenged as inadequate by defendants. This dynamic and the resulting motive that the court avoid creating perverse incentives only further bolsters the plaintiffs’ position—that defendants’ arguments challenging plaintiffs’ expert’s calculations on the statistics based on alleged deficiencies in the underlying data, which was produced by the county and defendants’ police department, are evidentiary issues going to the weight of the evidence and not to its admissibility.

Defendants’ motion to exclude expert testimony denied.

Johnson v. Holmes, Case No. 3:16-cv-00016, Aug. 23, 2022. WDVA at Charlottesville (Moon). VLW 022-3-365. 14 pp.

VLW 022-3-365

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