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					@ -13,7 +13,7 @@ from numpy import (isscalar, r_, log, sum, around, unique, asarray,
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					     floor, array, poly1d, compress, not_equal, pi, exp, ravel, angle)
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					     floor, array, poly1d, compress, not_equal, pi, exp, ravel, angle)
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					from numpy.testing.decorators import setastest
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					from numpy.testing.decorators import setastest
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					from scipy.lib.six import string_types
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					from scipy._lib.six import string_types
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					from ._numpy_compat import count_nonzero
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					from ._numpy_compat import count_nonzero
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					from scipy import optimize
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					from scipy import optimize
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					from scipy import special
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					from scipy import special
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					@ -2066,7 +2066,7 @@ def median_test(*args, **kwds):
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					    References
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					    References
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					    ----------
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					    ----------
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					    .. [1] Mood, A. M., Introduction to the Theory of Statistics. McGraw-Hill
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					    .. [1] Mood, A. M., Introduction to the Theory of Statistics. McGraw-Hill
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					        (1950), pp. 394-399. 
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					        (1950), pp. 394-399.
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					    .. [2] Zar, J. H., Biostatistical Analysis, 5th ed. Prentice Hall (2010).
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					    .. [2] Zar, J. H., Biostatistical Analysis, 5th ed. Prentice Hall (2010).
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					        See Sections 8.12 and 10.15.
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					        See Sections 8.12 and 10.15.
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					@ -2100,7 +2100,7 @@ def median_test(*args, **kwds):
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					           [11,  5, 10]])
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					           [11,  5, 10]])
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					    `p` is too large to conclude that the medians are not the same:
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					    `p` is too large to conclude that the medians are not the same:
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					    >>> p
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					    >>> p
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					    0.12609082774093244
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					    0.12609082774093244
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					@ -2120,7 +2120,7 @@ def median_test(*args, **kwds):
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					    >>> tbl
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					    >>> tbl
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					    array([[ 5, 11,  9],
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					    array([[ 5, 11,  9],
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					           [11,  4,  8]]) 
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					           [11,  4,  8]])
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					    This example demonstrates that if the data set is not large and there
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					    This example demonstrates that if the data set is not large and there
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					    are values equal to the median, the p-value can be sensitive to the
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					    are values equal to the median, the p-value can be sensitive to the
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