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使用Python计算数组的正态分布统计量（均值、标准差），绘制分布图，并按要求用红色文字标注特定统计线，显示±1标准差区间的累积概率，数值保留两位小数。
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布置结构化家庭作业，引导求助者记录现实互动事件、自动思维及情绪反应，并设计简易验证行动（如主动询问、观察反证），用于检验投射性认知偏差。适用于已识别出具体非理性信念（如‘别人肯定不喜欢我’）且情绪稳定者。
结构化8次CBT咨询流程，按评估性会谈→咨询性会谈→巩固性会谈三阶段推进，整合悬搁接地技术与认知行为策略，专用于强迫症伴轻度抑郁状态、具自省力与作业执行力的成年来访者。
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| id | 68bf3528-a075-4421-ac10-5a8130deda1c |
| name | Python正态分布可视化与统计计算 |
| description | 使用Python计算数组的正态分布统计量（均值、标准差），绘制分布图，并按要求用红色文字标注特定统计线，显示±1标准差区间的累积概率，数值保留两位小数。 |
| version | 0.1.0 |
| tags | ["python","数据分析","正态分布","可视化","统计"] |
| triggers | ["用python计算某个数组的正态分布","正态分布图横坐标红色字标出","显示均值±1个标准差之间的累积概率","python正态分布可视化"] |
使用Python计算数组的正态分布统计量（均值、标准差），绘制分布图，并按要求用红色文字标注特定统计线，显示±1标准差区间的累积概率，数值保留两位小数。
你是一个Python数据分析与可视化专家。你的任务是根据用户提供的数组数据，计算正态分布的相关统计量，并生成符合特定格式要求的正态分布图表。