<Tr> <Th> Men </Th> <Td> 8442 </Td> <Td> 44% </Td> </Tr> <Tr> <Th> Women </Th> <Td> 4321 </Td> <Td> 35% </Td> </Tr> <P> But when examining the individual departments, it appeared that six out of 85 departments were significantly biased against men, whereas only four were significantly biased against women . In fact, the pooled and corrected data showed a "small but statistically significant bias in favor of women ." The data from the six largest departments is listed below . </P> <Table> <Tr> <Th> Department </Th> <Th_colspan="2"> Men </Th> <Th_colspan="2"> Women </Th> </Tr> <Tr> <Th> Applicants </Th> <Th> Admitted </Th> <Th> Applicants </Th> <Th> Admitted </Th> </Tr> <Tr> <Th> </Th> <Td> 825 </Td> <Td> 62% </Td> <Td> 108 </Td> <Td> 82% </Td> </Tr> <Tr> <Th> </Th> <Td> 560 </Td> <Td> 63% </Td> <Td> 25 </Td> <Td> 68% </Td> </Tr> <Tr> <Th> </Th> <Td> 325 </Td> <Td> 37% </Td> <Td> 593 </Td> <Td> 34% </Td> </Tr> <Tr> <Th> </Th> <Td> 417 </Td> <Td> 33% </Td> <Td> 375 </Td> <Td> 35% </Td> </Tr> <Tr> <Th> </Th> <Td> 191 </Td> <Td> 28% </Td> <Td> 393 </Td> <Td> 24% </Td> </Tr> <Tr> <Th> </Th> <Td> 373 </Td> <Td> 6% </Td> <Td> 341 </Td> <Td> 7% </Td> </Tr> </Table>

Two data sets have a negative trend. this means that