@subsubheading Description

Aggregate data on applicants to graduate school at Berkeley for the six
largest departments in 1973 classified by admission and sex.

@subsubheading Format

A 3-dimensional array resulting from cross-tabulating 4526 observations on
3 variables. The variables and their levels are as follows:

@table @code
@item Admit
Admitted, Rejected.
@item Gender
Male, Female.
@item Dept
A, B, C, D, E, F.
@end table

@subsubheading Details

This data set is frequently used for illustrating Simpson's paradox, see
Bickel et al (1975). At issue is whether the data show evidence of sex bias
in admission practices. There were 2691 male applicants, of whom 1198 (44.5%)
were admitted, compared with 1835 female applicants of whom 557 (30.4%) were
admitted. This gives a sample odds ratio of 1.83, indicating that males were
almost twice as likely to be admitted. In fact, graphical methods (as in the
example below) or log-linear modelling show that the apparent association
between admission and sex stems from differences in the tendency of males
and females to apply to the individual departments (females used to apply
more to departments with higher rejection rates).

@subsubheading Source

The data are given in Box & Jenkins (1976). Obtained from the Time Series Data
Library at @url{http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/}.

@subsubheading References

Bickel, P. J., Hammel, E. A., and O'Connell, J. W. (1975). Sex bias in
graduate admissions: Data from Berkeley. @cite{Science}, 187, 398–403. 
@url{http://www.jstor.org/stable/1739581}.

@subsubheading Examples

@example
@INCLUDE_DATASET_EXAMPLE_SCRIPT{UCBAdmissions_1.m}
@end example
