• POWER
  • RISK
  • DATA
  • HUMAN

How to monitor test power and peeking risk with your AI

Stop guessing if your experiment is ready. Your AI handles the math to tell you if you have enough data or if you're just chasing noise.

Ask AI about this page

Short answer

How can I check my experiment's validity mid-run?

Your AI uses specific statistical tools to calculate your current power and the likelihood that you're seeing a false positive. This prevents you from calling a winner too early. You'll see exactly how much more data you need to reach confidence.

Where every result lands.

The outcomes of your analysis.

Your AI processes your raw experiment data into these four specific insights.

POWER

Statistical strength check

The AI calculates if your sample size is large enough to actually detect a difference. You'll know if your test is underpowered.

RISK

Peeking risk assessment

The AI identifies the danger of false positives caused by checking results too early. It tells you if your current significance is a fluke.

DATA

Required sample size

The AI determines how many more users or events you need to collect. This gives you a clear target for when to stop the test.

HUMAN

Decision support

The AI provides the math, but you decide whether to ship the change or keep running. It flags when the risk is too high to act.

The workflow

What your AI does when the data arrives.

Instead of you running manual formulas, your AI performs the heavy lifting on your experiment metrics.

  1. Evaluate sample strength

    The AI looks at your current conversion rates and sample sizes to see if the test has enough teeth.

    calculate_statistical_power

  2. Detect peeking errors

    The AI checks if your frequent monitoring is inflating the chance of a false positive.

    check_peeking_risk

  3. Project future needs

    The AI uses the current data to estimate the total volume required for a valid result.

    calculate_statistical_power

  4. Flag invalid results

    The AI alerts you if the current statistical strength is too low to trust the observed lift.

    check_peeking_risk

Try it

Copy these to start.

Use these prompts to kick off your analysis.

Starting points

Replace the bracketed text with your actual experiment details like your conversion rate or sample size.

A/B Test Significance Calculator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/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 — A/B Test Significance Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ab-test-significance-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"
    }
  }
}
Copy into chat04

  • Check the peeking risk for my current A/B test in this Google Sheet.

  • Calculate the statistical power for my experiment with a 5% conversion rate and 1,000 users.

  • How much more data do I need to reach 80% power for this test in my CSV file?

  • Is my current test result statistically significant, or am I peeking too early?

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

Start here

Connect A/B Test Significance Calculator once, then ask.

Connect your preferred client to the MCP in one click. Your credentials stay encrypted and secure while your AI gets direct access to your experiment data.

Connect A/B Test Significance Calculator to your AI

FAQ

How this task behaves.

  • 01

    Can the AI change my experiment settings in Optimizely?

    No. The AI only reads your data to perform calculations. It cannot modify your live experiments or any external tools.

  • 02

    Does the AI automatically stop my tests when they reach significance?

    No. The AI provides the math and the risk assessment, but you are the one who decides when to stop a test.

  • 03

    What kind of data do I need to provide?

    You need to provide your current sample sizes, conversion rates, and the baseline you are testing against.

  • 04

    Can it calculate power for multivariate tests?

    The current tools are designed for standard A/B tests to check power and peeking risk.

  • 05

    Will the AI delete my experiment logs?

    No. This MCP is read-only for your data. It has no capability to delete or overwrite your files.

  • More questions about A/B Test Significance Calculator? The Connector page answers them. See everything the A/B Test Significance Calculator Connector can do

Connect A/B Test Significance Calculator to Claude, Cursor, ChatGPT & more