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<Paper uid="M95-1004">
  <Title>STATISTICAL SIGNIFICANCE OF MUC-6 RESULT S</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> The results of the MUC-6 evaluation must be analyzed to determine whether close scores significantl y distinguish systems or whether the differences in those scores are a matter of chance. In order to do such an analysis , a method of computer intensive hypothesis testing was developed by SAIC for the MUC-3 results and has been use d for distinguishing MUC scores since that time . The implementation of this method for the MUC evaluations was firs t described in [1] and later the concepts behind the statistical model were explained in a more understandable manne r in [2] . This paper gives the results of the statistical testing for the three MUC-6 tasks where a single metric could b e associated with a system's performance .</Paragraph>
  </Section>
class="xml-element"></Paper>