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Statistical Tests – Normality Check
x402
Statistical Tests – Normality Check is a paid API for AI agents from stats-tests.x402tookit.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-21).
Screens a numeric sample for normality using skewness, excess kurtosis, Jarque-Bera test with p-value, and the 68-95-99.7 rule check.
Price / call$0.02
Success—
StatusUnknown
How this service works
Normality screen for a sample: skewness, excess kurtosis, Jarque-Bera test with p-value, and the 68-95-99.7 rule check.
Output
Returns a JSON object containing: sample size (n), mean, standard deviation, skewness, excess kurtosis, Jarque-Bera statistic, p-value, significance flag at 5%, percentages of values within 1/2/3 standard deviations, a human-readable verdict and summary, list of reasons supporting the verdict, any checks not performed, and optional degraded/disclaimer flags.
Example use cases
Pre-test assumption check for t-test
“Before I run a two-sample t-test, I need to verify normality — can you run a normality screen on these 30 measurements and tell me the Jarque-Bera result and p-value? Values: 101, 98, 103, 97, 105, 99, 102, 100, 104, 96, 101, 103, 98, 100, 99, 102, 97, 104, 101, 98, 103, 100, 99, 102, 97, 105, 101, 100, 98, 103”
Financial returns distribution screening
“I have daily portfolio returns for the past month and want to know if they're normally distributed — please check skewness, kurtosis, and give me the Jarque-Bera p-value for these values: 0.8, -0.3, 1.2, 0.5, -1.1, 2.4, 0.1, -0.7, 1.5, 0.3, -0.2, 0.9, 1.1, -0.5, 0.6, 0.4, -0.8, 1.3, 0.2, -0.4, 0.7, 0.0, -0.6, 1.0, 0.5, -0.9, 0.3, 1.4, -0.1, 0.8”
Quality control sample normality audit
“We're auditing a manufacturing process and need to know if these 20 unit weight measurements follow a normal distribution — run the normality check with the 68-95-99.7 rule and tell me the verdict: 250.1, 249.8, 250.3, 250.0, 249.9, 250.2, 250.5, 249.7, 250.1, 250.4, 249.6, 250.2, 250.0, 249.8, 250.3, 250.1, 249.9, 250.2, 250.0, 250.1”
Technical details
Endpoint
GEThttps://stats-tests.x402tookit.com/normality-check?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, comprehensive normality screen combining moment-based metrics (skewness, kurtosis), an omnibus test (Jarque-Bera), and an empirical rule check in a single call. Ideal as a pre-flight check before parametric tests (t-test, ANOVA, regression) that assume normality. Prefer this over manual calculation or generic statistics libraries when you need a structured, verdict-ready JSON response with p-values. For very large samples or formal hypothesis testing workflows, complement with the sibling endpoints for specific tests.
Side effects
- Fewer than 8 or more than 500 values provided — returns error or degraded result
- Non-numeric values in the sample — parsing failure
- Missing required 'values' query parameter — validation error
- Degenerate input (all identical values) — undefined skewness/kurtosis
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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