我需要计算p值，ods比率和95%置信区间矩阵2x2 usin python.我发现scipy.stats库

import scipy.stats as stats

v = [[8, 2], [1, 5]]
oddsratio, pvalue = stats.fisher_exact(v)

print(pvalue, oddsratio, sep="\n")  # 0.03496503496503495 and 20.0 (15.47 on R)

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但是我在计算95%置信区间时遇到了问题。我找到了scipy.stats.rv_continuous.interval方法

v_continuous.interval(self, alpha, *args, **kwds)[source]
    Confidence interval with equal areas around the median.

Parameters
    alphaarray_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).

    locarray_like, optional
    location parameter, Default is 0.

    scalearray_like, optional
    scale parameter, Default is 1.

Returns
    a, bndarray of float
    end-points of range that contain 100 * alpha % of the rv’s possible values.

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我试试下一个

a, b = stats.rv_continuous.interval(v, 0.95)
print(a, b, sep="\n")  # ~ 1.00884938039662 and 1049.79144613175 (calculated in R)

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但出现错误

a = self.ppf(q1, *args, **kwds)
AttributeError: 'list' object has no attribute 'ppf'

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我如何才能得到想要的结果？