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Scatter Graphs

Visualize relationships between two variables. Use for correlation analysis and pattern identification.
可视化两个变量之间的关系,用于相关分析和模式识别。
linuszz linuszz 来源
未分类 clawhub v1.0.0 1 版本 99761.9 Key: 无需
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概述

Scatter Graphs

Metadata

  • Name: scatter-graphs
  • Description: Correlation and relationship analysis
  • Triggers: scatter plot, correlation, relationship, XY chart

Instructions

Analyze relationships between variables for $ARGUMENTS using scatter graphs.

Framework

Scatter Plot Types

PatternMeaningAction
--------------------------
↑ PositiveDirect correlationLeverage relationship
↓ NegativeInverse correlationManage trade-off
○ NoneNo correlationLook for other factors
◐ ClusteredSegments existAnalyze separately

Correlation Strength

Strong Positive (r > 0.7):
    │     •
    │   • •
    │ • •
    │• •
    └──────

No Correlation (r ≈ 0):
    │  •   •
    │ •    •
    │   •  •
    │ •   •
    └──────

Output

## Scatter Analysis: [Variables]

### Data Summary

| X Variable | Y Variable | n | Correlation (r) |
|------------|------------|---|-----------------|
| Price | Volume | 50 | -0.65 |
| Ad Spend | Revenue | 50 | +0.72 |
| Size | Profit | 50 | +0.45 |

### Key Findings

**Relationship 1: Price vs Volume**
- Correlation: -0.65 (moderate negative)
- Interpretation: Higher price reduces volume
- Action: [Recommendation]

**Relationship 2: Ad Spend vs Revenue**
- Correlation: +0.72 (strong positive)
- Interpretation: Advertising drives revenue
- Action: [Recommendation]

### Outliers

| Observation | X | Y | Reason |
|-------------|---|---|--------|
| Store #12 | Very high | Low | New location |
| Store #23 | Low | High | Prime location |

### Implications

1. [Implication 1]
2. [Implication 2]

Tips

  • Check for causation vs correlation
  • Identify and investigate outliers
  • Consider non-linear relationships
  • Segment data if patterns differ

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-31 02:02 安全 安全

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