Data Processing
General Statistics Calculator
Paste one or two columns of numbers and get the complete descriptive suite — mean/median/mode, sample and population variance, type-7 quartiles and percentiles, MAD, adjusted skewness and kurtosis, Tukey outliers — plus covariance, Pearson r, tie-corrected Spearman rho and least-squares regression for two columns.
Quick start
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/general-statistics-calculator' \
-H 'Content-Type: application/json' \
-d '{"numbers":"2 4 4 4 5 5 7 9","datasetB":"","varianceBasis":"sample","decimalPlaces":4,"showOutliers":true}'API reference
Send a POST request with your inputs as JSON. File parameters require a separate upload first.
Endpoint
POST https://api.elysiatools.com/en/api/tools/general-statistics-calculatorParameters
| Name | Type | Required | Description |
|---|---|---|---|
| numbers | textarea | Yes | — |
| datasetB | textarea | No | — |
| varianceBasis | select | Yes | — |
| decimalPlaces | number | No | — |
| showOutliers | checkbox | No | — |
Response format
MCP integration
Add this tool to your Model Context Protocol server so AI agents can list and call it.
Server configuration
Add this block to your MCP client configuration:
{
"mcpServers": {
"elysiatools-general-statistics-calculator": {
"name": "general-statistics-calculator",
"description": "Paste one or two columns of numbers and get the complete descriptive suite — mean/median/mode, sample and population variance, type-7 quartiles and percentiles, MAD, adjusted skewness and kurtosis, Tukey outliers — plus covariance, Pearson r, tie-corrected Spearman rho and least-squares regression for two columns.",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=general-statistics-calculator",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}List available tools
After connecting to the SSE endpoint, list the exposed tools:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}Call this tool
Invoke the tool by its id, passing arguments built from its parameters:
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "general-statistics-calculator",
"arguments": {
"numbers": "2 4 4 4 5 5 7 9",
"datasetB": "",
"varianceBasis": "sample",
"decimalPlaces": 4,
"showOutliers": true
}
}
}