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XuetangX

数据时代的推断陷阱

via XuetangX

Overview

Learn to identify and navigate statistical pitfalls in the data age through a comprehensive 15-week course exploring data interpretation, visualization, and analysis. Master critical concepts including data ubiquity, quantification challenges, statistical graph interpretation, sampling methods, measurement validity, probability distributions, and real-world case studies. Examine famous historical examples of statistical misinterpretation, from election polls to medical studies, while developing skills to recognize common traps in data presentation and analysis. Explore practical applications through diverse case studies including clinical trials, scientific experiments, and criminal investigations, building expertise in avoiding statistical fallacies and making sound data-driven decisions.

Syllabus

  • 第一周
    • 1.1 无处不在的数据
    • 1.2 一切皆可量化
    • 1.3 让数据主宰一切的隐忧
  • 第二周
    • 1.4 直面统计陷阱
    • 2.1 三个典型图表陷阱
    • 2.2 图表的分类及常见的统计图表-1
  • 第三周
    • 2.3 常见的统计图表-2
    • 2.4 为数据配置统计图表
    • 2.5 常见的图表陷阱示例
  • 第四周
    • 3.1 样本中的陷阱
    • 3.2 抽样的基本概念、分类及非概率抽样方法
  • 第五周
    • 3.3 概率抽样方法
    • 3.4 抽样误差与非抽样误差
  • 第六周
    • 3.5 美国大选民调何以失真?
    • 4.1 度量的有效性
  • 第七周
    • 4.2 用数字特征概括数据—集中趋势
    • 4.3 用数字特征概括数据-离散程度
  • 第八周
    • 4.4 数据分布的形态
    • 4.5 五值概括法与盒型图
  • 第九周
    • 4.6 并非处处是正态
    • 5.1 关于机会结果的神话
  • 第十周
    • 5.2 血常规检验报告单中的置信区间
    • 5.3 女士品茶
  • 第十一周
    • 5.4 天空之眼
    • 5.5 易瑞沙——送给东亚人的礼物
    • 6.1 点球成金
  • 第十二周
    • 6.2 安斯库姆四重奏
    • 6.3 巧克力与获诺贝尔奖
    • 6.4 激素替代疗法的陷阱
  • 第十三周
    • 6.5 重返危机现场
    • 7.1 万能细胞
    • 7.2 智力的遗传判定
  • 第十四周
    • 7.3 密立根的实验笔记本
    • 7.4 “弑子案”的反转
  • 第十五周
    • 8.1 陷阱由何而生
  • 期末考试

    Taught by

    Shanghai University of Finance and Economics

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