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# scipy.stats.rv_continuous.interval

rv_continuous.interval(confidence, *args, **kwds)

  Confidence interval with equal areas around the median.

  Parameters:
    confidence array_like of float

      Probability that an rv will be drawn from the returned range. Each value should be in the range [0, 1].

    arg1, arg2, …array_like

      The shape parameter(s) for the distribution (see docstring of the instance object for more information).

    loc array_like, optional

      location parameter, Default is 0.

    scale array_like, optional

      scale parameter, Default is 1.

  Returns:
    a, b ndarray of float

      end-points of range that contain `100 * alpha %` of the rv’s possible values.

  Notes

  This is implemented as `ppf([p_tail, 1-p_tail])`, where `ppf` is the inverse cumulative distribution function and `p_tail = (1-confidence)/2`. Suppose `[c, d]` is the support of a discrete distribution; then `ppf([0, 1]) == (c-1, d)`. Therefore, when `confidence=1` and the distribution is discrete, the left end of the interval will be beyond the support of the distribution. For discrete distributions, the interval will limit the probability in each tail to be less than or equal to `p_tail` (usually strictly less).