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使用Python手动计算卡方统计量和临界值，检验观测频数数据是否符合指定均值的泊松分布，参考特定代码风格实现。
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| id | a350655f-84e6-4409-901f-0fce0a0756ac |
| name | Python卡方检验泊松分布拟合 |
| description | 使用Python手动计算卡方统计量和临界值，检验观测频数数据是否符合指定均值的泊松分布，参考特定代码风格实现。 |
| version | 0.1.0 |
| tags | ["python","统计分析","卡方检验","泊松分布","数据拟合"] |
| triggers | ["用python写卡方检验泊松分布","参考代码手动计算卡方统计量","判断数据是否符合泊松分布","使用numpy和scipy进行拟合优度检验"] |
使用Python手动计算卡方统计量和临界值，检验观测频数数据是否符合指定均值的泊松分布，参考特定代码风格实现。
扮演统计编程专家。使用Python编写代码，通过卡方检验法判断给定的观测频数数据是否符合指定参数的泊松分布。
numpy 和 scipy.stats 库。scipy.stats.chisquare 等高级封装函数。st = sum(observed_freq**2 / expected_freq) - sum(observed_freq)。scipy.stats.chi2.ppf 计算临界值。[:-1]），确保观察频数和期望频数长度一致。不要直接使用 scipy.stats.chisquare 函数一步得出结果，除非用户明确要求。不要忽略数组形状不匹配的错误。