January 2009 RIF at issue here, the raw statistics presented fall far short of permitting an inference of gender discrimination. Statistical analysis is rarely “sufficient to defeat summary judgment. Although a generalized statistical analysis of selections in a RIF can provide circumstantial evidence of an inference of discrimination in support of a prima facie case, as a matter of law, it is not sufficient to establish that the Defendant’s legitimate business rationale for eliminating Plaintiffs position is false, or that her ... gender was the real reason for her termination.” Zito v. Fried, Frank, Harris, Shriver & Jacobson, 869 F.Supp.2d 378, 395-96 (S.D.N.Y.2012) (citing Robinson v. Metro-North Commuter R.R., No. 94 Civ. 7374(JSR), 1998 WL 17742, at *9 (S.D.N.Y. Jan. 16, 1998) (<HOLDING>)). The statistics offered by Vuona and Wharton
holding that summary judgment was appropriate where plaintiffs statistical evidence which lacked specific analytical foundation and thus failed to show that employer maintained discriminatory intent was insufficient to establish prima facie case or pretext holding that plaintiffs statistical evidence failed to establish prima facie case or pretext where evidence failed to make specific analytical comparisons holding reliance on statistical evidence of inexorable zero was sufficient to establish prima facie case notwithstanding plaintiffs failure to reference appropriate workpool holding that while statistical evidence may sometimes enable a plaintiff to carry its modest burden of creating a prima facie case  the court is aware of no case where generalized statistical evidence has been held sufficient to refute for summary judgment purposes a defendants particularized evidentiary showing of a nondiscriminatory explanation for a particular act complained of holding the plaintiff satisfies the burden of a prima facie case by a preponderance of the evidence