\documentclass[11pt]{article}
\setlength{\oddsidemargin}{0.0truein}
\setlength{\evensidemargin}{0.0truein}
\setlength{\textwidth}{6.5truein}
\setlength{\topmargin}{0.0truein}
\setlength{\textheight}{9.0truein}
\setlength{\headsep}{0.0truein}
\setlength{\headheight}{0.0truein}
\setlength{\topskip}{10.0pt}
\usepackage{url}
\begin{document}
\begin{center}
  \textbf{\textsc{STANFORD UNIVERSITY}}\\[5pt]
  \textbf{\textsc{DEPARTMENT OF STATISTICS}}\\[5pt]
  \Large{\textbf\textsc{{DEPARTMENTAL SEMINAR}}}
\end{center}
\begin{center}
  4:15 p.m., Tuesday, May 10, 2005\\
  Sequoia Hall Room 200\\
  (Cookies at 3:45 in 1st Floor Lounge)
\end{center}

\begin{center}
  \textsl{Moshe Pollak}\\
  Department of Statistics\\
  The Hebrew University of Jerusalem\\
  Israil
\end{center}
\begin{center}
  \textbf{Sequential Selection Based on Ranks}
\end{center}


Often, when sitting in a hiring committee, a question asked is: "Does
the candidate improve the quality (average/median/etc.) of the
department?"  In general, the problem we consider in this talk is
sequential selection of candidates who show up in a random fashion,
where a decision must be made whether or not to hire a given candidate
before other candidates are interviewed, and once a decision is made
it cannot be revisited.  The procedures we consider are based on
ranks: after being interviewed, a candidate is ranked with respect to
her/his predecessors.  We consider selection rules that improve the
upper p-percent of the retained group (hence "PRANKS").  We describe
the evolution of the quality of the series (hence "SERIESLY") of hired
candidates and how quickly the retained group grows.

\end{document}