we find it unnecessary to decide whether the errors in computation, under these circumstances, are enough on their own to render the regression analysis inadmissible. 310 . See Daniel L. Rubinfeld, Reference Guide on Multiple Regression, in REFERENCE MANUAL ON SCIENTIFIC EVIDENCE 179, 181 (Federal Judicial Center 2000). Professor Rubinfeld notes that the failure to include “a major explanatory variable that is correlated with the variable of interest may cause an included variable to be credited with an effect that actually is caused by the excluded variable” and that this flaw in methodology may lead to "inferences made from regression analyses that do not assist the trier of fact.” Id. at 188. 311 . Judge Scheindlin cited Bickerstaff v. Vassay College, 196 F.3d 435, 450 (2d Cir.1999) (<HOLDING>); Smith v. Xerox Corp., 196 F.3d 358, 370-71
holding that a challenge for cause for actual bias  essentially requires a determination  of credibility holding that defendants right to crossexamine a witness for bias or motivation to lie is not grounds for reversal where the jury had enough information despite the limits placed on otherwise permitted crossexamination to assess the defense theory of bias or improper motive holding the bias analysis insufficient to support its decisions recognizing that statutes mandating recusal for actual bias have constitutional bases unlike those that require recusal for a mere appearance of bias or prejudice holding that assumption that race bias tainted professors course evaluation scores is untenable without attempting to control for oth er causes for low score