statistical_error_analysis
$
npx mdskill add InternScience/scp/statistical_error_analysis**Discipline**: Statistics | **Tools Used**: 5 | **Servers**: 1
SKILL.md
.github/skills/statistical_error_analysisView on GitHub ↗
---
name: statistical_error_analysis
description: "Statistical Error Analysis - Analyze measurement errors: absolute error, scientific notation, max value, mean square, and formatting. Use this skill for statistics tasks involving calculate absolute error convert to scientific notation calculate max value calculate mean square format scientific notation. Combines 5 tools from 1 SCP server(s)."
---
# Statistical Error Analysis
**Discipline**: Statistics | **Tools Used**: 5 | **Servers**: 1
## Description
Analyze measurement errors: absolute error, scientific notation, max value, mean square, and formatting.
## Tools Used
- **`calculate_absolute_error`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`convert_to_scientific_notation`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`calculate_max_value`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`calculate_mean_square`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`format_scientific_notation`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
## Workflow
1. Calculate absolute error
2. Convert to scientific notation
3. Find maximum value
4. Calculate mean square
5. Format results in scientific notation
## Test Case
### Input
```json
{
"measured": 14.7,
"true_val": 15.0,
"values": [
14.5,
14.7,
14.9,
15.1
]
}
```
### Expected Steps
1. Calculate absolute error
2. Convert to scientific notation
3. Find maximum value
4. Calculate mean square
5. Format results in scientific notation
## Usage Example
> **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).
```python
import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client
SERVERS = {
"server-26": "https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis"
}
async def connect(url, transport_type):
transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
read, write, _ = await transport.__aenter__()
ctx = ClientSession(read, write)
session = await ctx.__aenter__()
await session.initialize()
return session, ctx, transport
def parse(result):
try:
if hasattr(result, 'content') and result.content:
c = result.content[0]
if hasattr(c, 'text'):
try: return json.loads(c.text)
except: return c.text
return str(result)
except: return str(result)
async def main():
# Connect to required servers
sessions = {}
sessions["server-26"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis", "streamable-http")
# Execute workflow steps
# Step 1: Calculate absolute error
result_1 = await sessions["server-26"].call_tool("calculate_absolute_error", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Convert to scientific notation
result_2 = await sessions["server-26"].call_tool("convert_to_scientific_notation", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Find maximum value
result_3 = await sessions["server-26"].call_tool("calculate_max_value", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Calculate mean square
result_4 = await sessions["server-26"].call_tool("calculate_mean_square", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Step 5: Format results in scientific notation
result_5 = await sessions["server-26"].call_tool("format_scientific_notation", arguments={})
data_5 = parse(result_5)
print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
```