• PARAMETRIC
  • NON-PARAMETRIC
  • METRICS
  • HUMAN

How to verify sensor data distribution with your AI

Connect the Normality Test Engine to your AI client to automate statistical checks on incoming telemetry. Once connected, your agent handles the math to decide which statistical models to apply.

Ask AI about this page

Short answer

Can my AI tell if my sensor data is normally distributed?

Yes. Your AI uses the Normality Test Engine to run exact skewness and kurtosis calculations on your datasets. This tells you immediately if you can use standard parametric tests or if you need to switch to non-parametric methods.

Statistical outcomes

Where your results land.

The AI processes your raw sensor readings into these specific results.

PARAMETRIC

Normal distribution confirmed

The AI finds that skewness and kurtosis fall within acceptable bounds. You get the green light to use standard parametric statistical models.

NON-PARAMETRIC

Non-parametric requirement

The AI detects significant skew or kurtosis. It flags your data as requiring non-parametric methods to avoid biased results.

METRICS

Exact distribution values

The AI provides the specific skewness and kurtosis numbers. You get the raw statistical evidence used to make the distribution call.

HUMAN

Manual model selection

The AI identifies the distribution type, but you decide which specific downstream analytical model fits your specific use case.

The workflow

What your AI does when sensor data arrives.

Your agent takes the raw telemetry and runs a sequence of statistical checks to validate the data shape.

  1. Ingest telemetry

    Your AI pulls the latest sensor readings from your connected data source.

    test_normality

  2. Calculate shape

    The agent computes the exact skewness and kurtosis for the dataset.

    test_normality

  3. Evaluate normality

    The AI compares the calculated values against normal distribution thresholds.

    test_normality

  4. Recommend method

    The agent tells you whether to proceed with parametric or non-parametric testing.

    test_normality

Try it

Copy these to start.

Use these prompts to trigger the Normality Test Engine.

Starting points

Replace the bracketed text with your actual data source or file names.

Normality Test Engine Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_WUlfcwTW8ijdRBrYjBDTpDiFw1dcKsTz5HdufzbG/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Normality Test Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "normality-test-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_WUlfcwTW8ijdRBrYjBDTpDiFw1dcKsTz5HdufzbG/mcp"
    }
  }
}
Copy into chat04

  • Run a normality test on the sensor readings in my 'temperature_log.csv' file.

  • Check the distribution of the pressure data from the 'industrial_sensor_01' stream.

  • Based on the skewness of my recent voltage readings, should I use a parametric test?

  • Analyze the kurtosis for the vibration data in my SQL database and tell me if it's normal.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Normality Test Engine once, then ask.

Just link the MCP to your preferred client. Your credentials stay encrypted, and you can start running tests immediately.

Connect Normality Test Engine to your AI

FAQ

How this task behaves

  • 01

    Can the AI change my raw sensor data?

    No. The AI only reads the data to perform calculations. It cannot modify your original sensor logs or database entries.

  • 02

    Does the AI pick the final statistical model?

    No. The AI identifies if the data is normal or not, but you must choose which specific downstream model to apply to your analysis.

  • 03

    What specific values does it calculate?

    The AI calculates exact skewness and kurtosis to determine the distribution shape.

  • 04

    Can I use this with any data file?

    The AI can process any data you provide through your connected client, provided the data is accessible to the agent.

  • 05

    Does it handle outliers automatically?

    The AI includes outliers in its skewness and kurtosis calculations, which is how it identifies non-normal distributions.

  • More questions about Normality Test Engine? The Connector page answers them. See everything the Normality Test Engine Connector can do

Connect Normality Test Engine to Claude, Cursor, ChatGPT & more