假设追踪器

概述

假设追踪器技能为制定、测试和验证业务假设提供系统化能力。它通过管理假设从制定到解决的生命周期，支持业务决策的科学方法。

能力

假设制定协助
测试设计规范
证据收集与关联
置信度追踪
假设状态管理
无效化标准定义
学习文档化
假设仪表板

使用流程

假设驱动分析流程
A/B测试与实验框架
决策文档与学习

使用方法

假设制定

# 创建假设
hypothesis = {
    "id": "HYP-2024-001",
    "title": "价格弹性假设",
    "statement": "10%的价格降低将使单位销量增加超过15%，从而提高总收入",
    "context": {
        "business_question": "我们是否应该降低价格以扩大市场份额？",
        "decision_at_stake": "第二季度定价策略",
        "stakeholders": ["销售副总裁", "首席财务官", "产品经理"]
    },
    "structure": {
        "independent_variable": "价格",
        "dependent_variable": "单位销量, 总收入",
        "mechanism": "需求价格弹性 > 1.5",
        "conditions": "在当前市场条件下，针对现有产品线"
    },
    "created_by": "产品经理",
    "created_date": "2024-01-15",
    "status": "测试中",
    "priority": "高"
}

证伪标准

# 定义什么会证伪该假设
falsification_criteria = {
    "hypothesis_id": "HYP-2024-001",
    "criteria": [
        {
            "type": "主要",
            "criterion": "10%降价后单位销量增长 < 15%",
            "measurement": "比较价格变化前后30天的销量",
            "threshold": 0.15
        },
        {
            "type": "次要",
            "criterion": "尽管销量增加但总收入下降",
            "measurement": "前后收入对比",
            "threshold": 0
        },
        {
            "type": "有效性检查",
            "criterion": "无混杂事件（竞争对手行动、季节性）",
            "measurement": "市场监控、历史对比"
        }
    ],
    "minimum_evidence": "主要标准必须用n>1000笔交易进行测试"
}

测试设计

# 定义测试方法
test_design = {
    "hypothesis_id": "HYP-2024-001",
    "test_type": "A/B测试",
    "design": {
        "control_group": "现有价格（$100）",
        "treatment_group": "降低价格（$90）",
        "sample_size": {"control": 5000, "treatment": 5000},
        "duration": "30天",
        "randomization": "客户ID哈希",
        "primary_metric": "销售单位数",
        "secondary_metrics": ["收入", "利润率", "客户获取"]
    },
    "statistical_plan": {
        "significance_level": 0.05,
        "power": 0.80,
        "minimum_detectable_effect": 0.12,
        "analysis_method": "双样本t检验"
    },
    "timeline": {
        "start_date": "2024-02-01",
        "end_date": "2024-03-02",
        "analysis_date": "2024-03-05"
    }
}

证据收集

# 记录证据
evidence = {
    "hypothesis_id": "HYP-2024-001",
    "evidence_items": [
        {
            "id": "EV-001",
            "date": "2024-03-05",
            "type": "实验结果",
            "source": "A/B测试分析",
            "finding": "实验组显示单位销量增长18.2%",
            "confidence_interval": [0.142, 0.222],
            "p_value": 0.001,
            "supports_hypothesis": True,
            "strength": "强"
        },
        {
            "id": "EV-002",
            "date": "2024-03-05",
            "type": "实验结果",
            "source": "A/B测试分析",
            "finding": "尽管降价10%，总收入仍增长6.4%",
            "confidence_interval": [0.031, 0.097],
            "p_value": 0.02,
            "supports_hypothesis": True,
            "strength": "中等"
        },
        {
            "id": "EV-003",
            "date": "2024-02-20",
            "type": "市场观察",
            "source": "竞争情报",
            "finding": "测试期间无竞争对手价格变化",
            "supports_hypothesis": True,
            "strength": "支持性背景"
        }
    ]
}

假设解决

# 解决假设
resolution = {
    "hypothesis_id": "HYP-2024-001",
    "resolution_date": "2024-03-10",
    "outcome": "已验证",
    "confidence": 0.95,
    "summary": "A/B测试结果支持该假设。18.2%的销量增长超过15%阈值，收入增长6.4%。",
    "decision_recommendation": "为整个产品线推进降价",
    "caveats": [
        "结果基于30天周期，长期效果未知",
        "测试在稳定市场进行，在竞争反应下可能不成立"
    ],
    "learnings": [
        "该产品类别的价格弹性约为1.8",
        "客户获取改善12%，表明价值感知影响"
    ],
    "follow_up_hypotheses": [
        "HYP-2024-002：降价效果持续6个月",
        "HYP-2024-003：相邻产品线存在类似弹性"
    ]
}

输入模式

{
  "operation": "create|update|evidence|resolve|report",
  "hypothesis": {
    "title": "string",
    "statement": "string",
    "context": "object",
    "structure": "object"
  },
  "falsification_criteria": ["object"],
  "test_design": "object",
  "evidence": ["object"],
  "resolution": "object"
}

输出模式

{
  "hypothesis": {
    "id": "string",
    "status": "string",
    "confidence": "number"
  },
  "evidence_summary": {
    "supporting": "number",
    "contradicting": "number",
    "neutral": "number"
  },
  "dashboard": {
    "active_hypotheses": "number",
    "pending_tests": "number",
    "validated_this_quarter": "number",
    "invalidated_this_quarter": "number"
  },
  "learnings": ["string"]
}

假设状态生命周期

状态	描述
草稿	正在制定中
就绪	已定义证伪标准
测试中	进行中的活动测试
分析中	测试完成，正在分析结果
已验证	证据支持假设
已证伪	证据与假设矛盾
不确定	任一方向的证据不足
已归档	不再相关

最佳实践

使假设具体且可测试
预先定义证伪标准
区分相关性与因果关系
记录负面结果 - 它们很有价值
将假设与它们所影响的决策联系起来
用后续假设建立在已验证假设的基础上
定期审查假设组合

集成点

输入到实验管理器代理
与因果推理引擎连接进行分析
支持决策日志进行知识捕获
与决策归档器集成进行学习