E.E.O.C. v. American Nat. Bank, 79-1533

Citation680 F.2d 965
Decision Date18 May 1982
Docket NumberNo. 79-1533,79-1533
Parties30 Fair Empl.Prac.Cas. 906, 29 Empl. Prac. Dec. P 32,720 EQUAL EMPLOYMENT OPPORTUNITY COMMISSION, Appellant, v. AMERICAN NATIONAL BANK, Appellee.
CourtUnited States Courts of Appeals. United States Court of Appeals (4th Circuit)

On Suggestion for Rehearing En Banc.

Constance L. Dupre, Acting Gen. Counsel, Philip B. Sklover, Acting Associate Gen. Counsel, Vella M. Fink, Asst. Gen. Counsel, William H. Ng, Washington, D. C., for appellant.

Paul M. Thompson, Thomas J. Manley, Gregory B. Robertson, Hunton & Williams, Richmond, Va., for appellee.

ORDER

The appellee's petition for rehearing and suggestion for rehearing en banc has been considered by the court.

The panel considered the petition for rehearing and decided, Judge Russell dissenting, that it should be and it is denied.

On a poll of the court on the suggestion for rehearing en banc, the court was evenly divided. Because a majority of the judges in regular active service did not vote in favor of rehearing en banc, that suggestion in motion is denied. From this denial, Judge Russell, Judge Widener, Judge Hall, Judge Ervin and Judge Chapman dissent, and Judge Widener has filed a dissenting opinion in which Judge Russell joins.

Entered at the direction of Judge Phillips.

WIDENER, Circuit Judge, dissenting:

I would respectfully add a word of dissent.

I dissent because there are significant errors in both the district court and panel opinions concerning the appropriate use of statistical evidence in employment discrimination cases. These errors, I think, may only, at best, confuse the law of employment discrimination in this circuit.

The errors in using the statistics are two-fold. First, the district court failed to employ a proper statistical analysis in arriving at its conclusion that the employment statistics demonstrated a prima facie case of employment discrimination. The panel majority compounded this error when it adopted the district court's finding. Second, this majority erred in its use of statistical rebuttal evidence. Correct statistical analysis shows that the EEOC never demonstrated a prima facie case here (especially for Suffolk), and assuming, arguendo, that a prima facie case was presented, the defendant provided sufficient rebuttal evidence. 1

I. Prima Facie Case

The Supreme Court has reasoned that statistical evidence may alone establish a prima facie case of racial discrimination. See, e.g., Hazelwood School District v. United States, 433 U.S. 299, 307-08, 97 S.Ct. 2736, 2741, 53 L.Ed.2d 768 (1977); Teamsters v. United States, 431 U.S. 324, 339, 97 S.Ct. 1843, 1856, 52 L.Ed.2d 396 (1977). Nevertheless, it is essential that a court's utilization of statistics be mathematically correct in order to prevent an invalid conclusion. In the instant case, the district court found a prima facie case of discrimination exclusively on the basis of employment statistics. 2 The court compared the percentage of blacks in the defendant's office/clerical work force to the percentage of blacks in comparable jobs in the respective geographic areas. It concluded:

that there has been consistent underrepresentation of blacks on the work force of defendant between 1969 and 1975... The fact remains ... that the percentage of blacks in defendant's total work force has remained at least 15 percent below the percentage of blacks in the available work force of any of the communities comprising the two relevant labor market areas.

EEOC v. American National Bank, 21 E.P.D. (CCH) P 30,369 at 13,057 (E.D.Va., June 25, 1979). The opinion continued "The Court finds, therefore, that the statistical evidence presented here by the EEOC is prima facie statistical proof of a pattern or practice of discrimination." Id. at 13,058.

The panel majority followed the district court and adopted the finding of a prima facie case, concluding:

These statistical disparities are substantial, in some cases reaching the 'inexorable zero' point. Teamsters, 431 U.S. at 342 n. 23 (97 S.Ct. at 1858 n. 23). They show that blacks were consistently underrepresented in the office and clerical categories in branches in both cities and underrepresented in the officials and managers categories in Suffolk all years and Portsmouth for four of seven years. The district court's conclusion, that considered alone, they establish a prima facie case is firmly supported by the record. (Emphasis added).

EEOC v. American National Bank, 652 F.2d 1176, 1190 (4th Cir. 1981).

In my opinion the conclusions of the panel majority and that of the district court are equally incorrect.

In reaching their conclusions using straight percentage comparisons of actual and expected percentages of minority employees the courts contravened both common statistical principles and Supreme Court precedent. Statisticians do not simply look at two figures, in this case the actual percentage of black employees compared with the percentage available, and make a subjective conclusion, as did the courts here, that the figures are significantly different. Rather, statisticians compare figures through an objective process known as hypothesis testing. C. Hicks, Fundamental Concepts in the Design of Experiments, 15 (1973) (hereinafter Hicks); F. Mosteller, R. Rourke & G. Thomas, Probability With Statistical Applications 302-05 (2d ed. 1970) (hereinafter Mosteller, Rourke & Thomas); R. Winkler & W. Hays, Statistics: Probability, Inference, and Decision, 402-03 (2d ed. 1975) (hereinafter Winkler & Hays). The process of hypothesis testing is readily adapted to employment discrimination statistics as they follow regular statistical formulae. See W. Connolly & D. Peterson, Use of Statistics in Equal Employment Opportunity Litigation, 74-83 (1980) (hereinafter Connolly & Peterson).

In hypothesis testing, the statistician sets a null hypothesis, which he subsequently seeks to disprove through the use of various objective mathematical formulae. Hicks, supra at 15-16; Mosteller, Rourke & Thomas, supra at 303-04. If the hypothesis is disproven, the statistician can state, to a given precision, that the two statistics are in fact different. Hicks, supra at 16; Mosteller, Rourke & Thomas, supra at 305-06. In the situation of racial employment discrimination statistics, the null hypothesis is that the actual and expected percentages of minority employees are equal. If the null hypothesis is rejected, then one can say, with a given precision, that the difference between the two percentages is not the result of random chance.

The process of hypothesis testing is not an academic exercise for substituting objective mathematical criteria for the judgment of a court of law. Rather, it is a means of according mathematical credibility to statistical evidence used in the litigation process. It is axiomatic in statistical analysis that the precision and dependability of statistics is related to the size of the sample being tested. K. Hammond & J. Householder, Introduction to the Statistical Method, 299 (1962) (hereinafter Hammond & Householder); Winkler & Hays, supra at 444-47. 3 Without the use of hypothesis testing, a court may accord credibility in law to statistics which are not deserving of mathematical credibility. Such a situation often arises when the employment situation under consideration involves a small number of people, such as in the instant case. 4

The Supreme Court has recognized the danger of making comparisons between the percentages of minority population without further mathematical analysis. In Mayor v. Educational Equality League, 415 U.S. 605, 94 S.Ct. 1323, 39 L.Ed.2d 630 (1974), the Court reversed a court of appeals finding of discrimination in the make-up of a commission to nominate members of the Philadelphia school board. The court of appeals had found it significant that while 60% of the school population was black and 34% of the city's population was black, only 15% of the 13 member nominating board was black. The Supreme Court said: "(T) he District Court's concern for the smallness of the sample represented by the 13 member panel was well founded. The Court of Appeals erred in failing to recognize the importance of this flaw in straight percentage comparisons." Id. at 621, 94 S.Ct. at 1333 (emphasis added).

In the instant case, both the district court and the panel majority, in finding a prima facie case had been proven by statistics, committed the same error of drawing conclusions from straight percentage comparisons without taking into account sample size at all. 5 That majority justified its finding of a prima facie case through the use of straight percentage comparisons by saying:

As frequently observed by the Supreme Court, and as recognized by the district court, gross statistical disparities in the static work force during the relevant period may alone constitute prima facie proof of the discriminatory practice. Hazelwood, 433 U.S. at 307-08 (97 S.Ct. at 2741); Teamsters, 431 U.S. at 335 n. 15, 339 n. 20 (97 S.Ct. at 1854 n. 15, 1856 n. 20); Arlington Heights v. Metropolitan Housing Development Corp., 429 U.S. 252, 265-66 (97 S.Ct. 555, 563, 55 L.Ed.2d 450) (1976).

652 F.2d at 1189. The panel majority and the district court before it, however, did not consider a footnote in Hazelwood where the Supreme Court explained the meaning of statistical disparity. The Supreme Court said, "A precise method of measuring such statistical disparities was explained in Castaneda v. Partida, 430 U.S. 482, 496-497 n. 17, 97 S.Ct. 1272, 1281 n. 17, 51 L.Ed.2d 498. It involves the calculation of the 'standard deviation' as a measure of the predicted fluctuations from the sample." 433 U.S. at 309, n. 14, 97 S.Ct. at 2742, n. 14. Clearly then the term "gross statistical disparity" in the Hazelwood opinion does not mean a seemingly large difference in straight percentage comparisons; it means disparities must be found at the conclusion of statistical analysis using standard...

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