
    DL, et al., Plaintiffs, v. DISTRICT OF COLUMBIA, et al., Defendants.
    Civil Action No. 05-1437 (RCL).
    United States District Court, District of Columbia.
    Aug. 10, 2010.
    
      Alexander R. Karam, Bruce J. Terris, Terris, Pravlik & Millian, L.L.P., Jeffrey S. Gutman, The George Washington University Law School, Margaret A. Kohn, Washington, DC, for Plaintiffs.
    Daniel Albert Rezneck, Robert C. Utiger, Samuel C. Kaplan, Sarah Ann Sulkowski, Office of the Attorney General, DC, Washington, DC, for Defendants.
   MEMORANDUM OPINION

ROYCE C. LAMBERTH, Chief Judge.

Before the Court is Defendants’ Motion [181] to Strike Report and Testimony of Dr. Leonard Cupingood, Along with All Evidence Based Thereon. Upon consideration of the motion, plaintiffs’ opposition [184] thereto, defendants’ reply brief [190], and plaintiffs’ surreply brief [191-2], the Court will deny the motion for the reasons set forth below.

I. BACKGROUND

The Court set out the background of this case in its memorandum opinion issued this same date regarding defendants’ motion for summary judgment and plaintiffs’ motion for partial summary judgment on liability.

At issue here is the testimony of plaintiffs’ statistical expert, Dr. Leonard A. Cupingood. Dr. Cupingood reviewed data from two databases, covering the time period of 2000 to 2009, to assess the number of children in the District ages 3 to 5 “with suspected disabilities who were to be assessed for their eligibility for special education and related services.” (Bernard R. Siskin and Leonard A. Cupingood, Statisti cal Analysis of Timeliness of Assessment of Eligibility for Special Education Services for Children Aged Three to Five in the District of Columbia Public Schools 2000-2008 (April 2009) (“Cupingood Report”) at 2.) Before beginning his analysis, Dr. Cupingood “cleaned” the data by, inter alia, “consolidating approximately 130 records having a complete duplication of all information except for the student ID.” (Cupingood Aff., May 18, 2010 (“Cupingood Aff.”) at ¶ 8.) Dr. Cupingood then analyzed the data, the results of which the Court relied on in its summary judgment opinion issued this same date.

II. LEGAL STANDARD

The Court may qualify an expert on the basis of his “knowledge, skill, experience, training, or education.” Fed. R.Evid. 702. Plaintiffs have the burden of establishing by a preponderance of the evidence that the expert is so qualified and that the testimony is admissible. Meister v. Med. Eng’g Corp., 267 F.3d 1123, 1127 n. 9 (D.C.Cir.2001); Fed.R.Evid. 702 advisory committee’s notes to 2000 amend.

The relevant Federal Rules of Evidence governing expert testimony state:

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 ... may testify thereto in the form of an opinion or otherwise, if (1) the testimony is based upon sufficient facts or data, (2) the testimony is the product of reliable principles and methods, and (3) the witness has applied the principles and methods reliably to the facts of the case.

Fed.R.Evid. 702.

The facts or data in the particular case upon which an expert bases an opinion or inference may be those perceived by or made known to the expert at or before the hearing. If of a type reasonably relied upon by experts in the particular field in forming opinions or inferences upon the subject, the facts or data need not be admissible in evidence in order for the opinion or inference to be admitted. Facts or data that are otherwise inadmissible shall not be disclosed to the jury by the proponent of the opinion or inference unless the court determines that their probative value in assisting the jury to evaluate the expert’s opinion substantially outweighs their prejudicial effect.

Fed.R.Evid. 703.

III. DISCUSSION

As a preliminary matter, plaintiffs argue that the Court may postpone ruling on this motion until trial. (Pis.’ Opp’n at 14.) The Court, however, relies on Dr. Cupingood’s testimony in its summary judgment order issued this same date. Accordingly, the Court will rule on the admissibility of Dr. Cupingood’s opinions now, and it will not wait until any possible trial.

A. QUALIFICATION AS AN EXPERT

First, defendants challenge Dr. Cupingood’s qualification as a “programming or data expert.” (Defs.’ Mot. at 10; Defs.’ Reply at 3.) Plaintiffs contend that he is such an expert. The Court agrees with defendants.

The Court may look directly to Dr. Cupingood’s testimony in determining whether the expert is so qualified, see United States v. Pansier, 576 F.3d 726, 738 (7th Cir.2009), as well as other evidence. Dr. Cupingood testified only that he has “more than 35 years of experience with computers, computer programming and databases.” (Cupingood Aff. at ¶ 13.) He was also a court-appointed consultant to the U.S. District Court for the Eastern District of Pennsylvania, where he “advised the court regarding the adequacy of a computer system(Pis.’ Ex. K at 2; Pis.’ Ex. L at 27.) Finally, Dr. Cupingood has been qualified as an expert in other courts to testify “regarding database construction and programming.” (Cupingood Aff. at ¶ 13.)

Although Dr. Cupingood may in fact be an expert in computer programming, plaintiffs have not met their burden of establishing his expertise. They have cited sparse evidence of his experience, and Dr. Cupingood has conclusively stated that he has 35 years experience, without further explanation of what that experience entails. Accordingly, the Court finds that Dr. Cupingood is not qualified as an expert in computer programming.

Second, defendants concede that Dr. Cupingood is an expert in statistics. (Defs.’ Mot. at 10 (“Dr. Cupingood is a statistical expert.”); Defs.’ Mot. at 12.) Dr. Cupingood has an extensive resume to support this expertise. Accordingly, the Court finds that Dr. Cupingood is an expert in statistics.

B. BASIS OF EXPERT OPINION

Defendants challenge the basis upon which Dr. Cupingood formed his expert opinion. Specifically, defendants allege that:

(1) Dr. Cupingood’s opinions are based upon improperly ‘cleaned,’ and therefore useless, data; (2) Dr. Cupingood is not the author of the report submitted in his name, nor did he perform the calculations described therein; and (3) in any event, the matters on which Dr. Cupingood purports to opine are not properly the subjects of statistical expertise, as the Court is perfectly able to evaluate these data and decide these issues without expert assistance or, at most, with the very limited assistance of a computer-programming expert.
(Defs.’ Mot. at 1.) Defendants further allege in their reply that Dr. Cupingood’s charts and tables summarizing his calculations are inadmissible. The Court will address these arguments in turn.

1. Dr. Cupingood Did Not Rely on Improperly “Cleaned” Data.

Defendants argue that Dr. Cupingood improperly eliminated potentially duplicate records, so the data on which he based his opinion was improperly “cleaned.” Plaintiffs argue that Dr. Cupingood’s decision to eliminate these records was based on generally accepted statistical methods and did not significantly affect his conclusions. The Court agrees with plaintiffs.

Dr. Cupingood received extracts from two databases (“ENCORE” and “SEDS”) to perform his analysis. (Cupingood Report at 2.) Of all of the 12,340 entries in these databases, there were 130 records for which there was “complete duplication of information, as identified by having the same date of birth, year, referral date, eligibility status, eligibility date, initial IEP date, notice of placement date, hearing request date, hearing decision dates, services provided date and services,” and in which the “duplicate records were associated with more than one student ID.” (Id. at 7.) Dr. Cupingood concluded that “[wjhile it is theoretically possible that such duplicate information could be valid (e.g., identical twins for whom the referral and other dates were exactly the same), it is unlikely that they would have the exact same services provided on the same dates.” (Id.) Before reaching this conclusion, Dr. Cupingood asked plaintiffs’ attorney for his thoughts on the matter, and attorney Alexander Karam responded that he thought it was more likely that these were duplicate entries than identical twins. (Defs.’ Ex. B; Defs.’ Ex. A at 109-10.) Because Dr. Cupingood concluded that these were duplicate entries, he “only-counted such student records once, instead of multiple times.” (Cupingood Report at 7.) Dr. Cupingood stated that these entries were not necessarily duplicates in every instance, but it was more likely than not that they were mostly duplicates. (Defs.’ Ex. A at 82-83.)

Dr. Cupingood stated that this is a common way for a statistician to ensure the accuracy of his work: “[P]rior to conducting analyses, a statistician should examine the database provided for inconsistencies, duplicate information, erroneous data entries, and other situations where the database (or portions of the database) just do not make sense.” (Cupingood Aff. at ¶ 7.) This is logical. Based on solely the Court’s common sense, it would appear that, based on the large amount of duplicative information in these entries, the majority of these entries were in fact duplicates.

Defendants also argue that Dr. Cupingood relied on a computer programmer named Bryan Niederberger to assist him with “cleaning” the data. (Defs.’ Mot. at 9.) Even if Dr. Cupingood relied on Mr. Niederberger to help write computer code and carry out analyses, the Court finds that such reliance is permissible. An expert may rely on evidence if “of a type reasonably relied upon” by experts in the field, Fed.R.Evid. 703, and this evidence may include analyses carried out by assistants, McReynolds v. Sodexho Marriott Servs., 349 F.Supp.2d 30, 36-37 (D.D.C.2004) (Huvelle, J.).

Finally, any statistical error created by any improper “cleaning” is de minimis. There are only 130 entries in dispute, and Dr. Cupingood analyzed 12,340 entries. (Cupingood Aff. at ¶ 14.) Dr. Cupingood calculated that if he were to include the deleted entries in his calculations, the resulting calculations would be less than 1% different from the calculations provided in his expert report. (Id. at ¶ 12.) In fact, to the District’s detriment, the resulting calculations would actually show that the District had a higher rate of failing to provide services than previously calculated. Any minor change in this statistical calculus would not change the Court’s ruling this same date as to summary judgment on liability.

2. Dr. Cupingood is the Author of the Report Submitted in His Name.

First, defendants allege that Dr. Cupingood did not write his own expert report. Rather, they allege that his subordinate, Mr. Niederberger, wrote the report. The only evidence that defendants cite in support of this claim is an e-mail in which Mr. Niederberger states: “The data has been cleaned up, but since [Dr. Cupingood’s] name is going on the report, I want to get [his] approval on the cleaned up data before I produce any numbers.” (Defs.’ Ex. D at 1.) Dr. Cupingood, however, stated that he, not Mr. Niederberger, wrote his own report. (Pis.’ Ex. I at 52-54.) Mr. Niederberger confirmed this fact, clarifying that he was not authoring the report, but rather looking for the approval of his supervisor, Dr. Cupingood. (Pis.’ Ex. F at ¶ 4.) The Court finds this explanation convincing. In forming his statistical expert opinion, Dr. Cupingood may rely on data provided by a subordinate computer programmer. See McReynolds, 349 F.Supp.2d at 36-37; see also Fed.R.Evid. 702 (an expert may rely on facts or data “of a type reasonably relied upon by experts in the particular field in forming opinions or inferences upon the subject”).

Second, defendants allege that someone named “Ihe” was involved in authoring Dr. Cupingood’s report. In so doing, defendants point to an e-mail in which Mr. Niederberger wrote: “Once Ihe and I sit down and talk we should be able to get you your answer.” (Defs.’ Ex. D at 1.) Plaintiffs provide the very reasonable explanation that the word “Ihe” in an e-mail was a typo, and Mr. Niederberger instead meant to write “he.” Dr. Cupingood confirmed this typo in his affidavit. (Cupingood Aff. at ¶ 4.) This quibble does not require serious debate. The Court agrees with plaintiffs that the word “Ihe” was a typo, and there was never someone named Ihe involved in the preparation of the report.

3. Dr. Cupingood’s Testimony Is a Proper Subject of Statistical Expertise.

Defendants claim that Mr. Cupingood’s only contribution was to “count,” which does not require expertise. Plaintiffs argue that the quantity of data makes counting impractical, if not impossible, and that the field of statistics includes such counting activity. The Court agrees with plaintiffs.

Federal Rule of Evidence 702 governs the question of whether testimony is helpful to the Court, and thus a proper subject of expert testimony. The Rule states that an expert may use “scientific, technical, or other specialized knowledge” if it “will assist the trier of fact to understand the evidence or to determine a fact in issue.” FED. R. EVID. 702. The advisory committee’s notes to Rule 702 state:

Whether the situation is a proper one for the use of expert testimony is to be determined on the basis of assisting the trier. There is no more certain test for determining when experts may be used than the common sense inquiry whether the untrained layman would be qualified to determine intelligently and to the best possible degree the particular issue without enlightenment from those having a specialized understanding of the subject involved in the dispute. When opinions are excluded, it is because they are unhelpful and therefore superfluous and a waste of time.

Fed. R. Evid. 702 advisory committee’s notes (internal citations omitted). Statistics can be a proper subject of expert testimony when they are helpful in a particular case to a trier of fact. See Adams v. Ameritech Servs., Inc., 231 F.3d 414 (7th Cir.2000); City of Tuscaloosa v. Harcros Chems., Inc., 158 F.3d 548 (11th Cir.1999).

The Court finds that Dr. Cupingood’s testimony is helpful to the Court in understanding the database at issue. First, the high quantity of data makes counting impractical. The database consists of 12,340 entries. Although it technically would be feasible for the Court to “count” the data and reach very elementary statistical conclusions without Dr. Cupingood’s expertise, this would be a waste of time and possibly would lead to unfounded conclusions. Dr. Cupingood’s testimony is very helpful to the Court in distilling conclusions from this large set of data. Second, the field of statistics includes this “counting” activity. A statistician’s purpose is to “count” by sorting through raw data and putting it in a more digestible format. He can present statistical conclusions that are not evident on the face of the data.

4. Defendants’ Argument that Dr. Cupingood’s Tables and Charts Are Not Admissible is Moot.

Plaintiffs argue that “if the Court decides not to rule on the admissibility of Dr. Cupingood’s opinions as expert testimony at this time, it can still consider Dr. Cupingood’s summary charts and tables.” (Pis.’ Opp’n at 15.) Because the Court will rule on the admissibility of the testimony now, this argument is moot.

IV. CONCLUSION

Accordingly, the Court will grant in part and deny in part defendants’ motion. The Court will order that Dr. Leonard Cupingood is qualified as an expert in statistics, but he is not qualified as an expert in computer programming. The Court will order that Dr. Cupingood’s testimony is admissible.

A separate Order consistent with this Memorandum Opinion shall issue this date.  