# Hypothesis Testing

> Take a user-stated hypothesis and test it against the data, producing a report stating whether the data supports, refutes, or is inconclusive about the claim. Use when the user has a specific question or claim they want to interrogate against a dataset.

- **Type:** Skill
- **Install:** `agentstack add skill-danielrosehill-claude-data-analyst-plugin-hypothesis-testing`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [danielrosehill](https://agentstack.voostack.com/s/danielrosehill)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [danielrosehill](https://github.com/danielrosehill)
- **Source:** https://github.com/danielrosehill/Claude-Data-Analyst-plugin/tree/master/skills/hypothesis-testing

## Install

```sh
agentstack add skill-danielrosehill-claude-data-analyst-plugin-hypothesis-testing
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Hypothesis Testing

Rigorous first-pass evaluation of a user hypothesis against a dataset.

## Inputs

- Path to a dataset file or folder.
- The **hypothesis**, stated in natural language (e.g. "customers in segment A spend more than those in segment B", "there's no difference in conversion by landing page").
- Optional: desired significance level α (default 0.05).

## Step 1 — Formalise the hypothesis

Before testing, restate the user's claim as:

- **H₀ (null)**: typically "no effect" / "no difference" / "no relationship".
- **H₁ (alternative)**: the user's claim, one- or two-sided as appropriate.
- **Variables involved**: identify which columns map to the hypothesis, with their dtypes.
- **Test type** selected based on the data shape (see decision table below).

Show this formalisation to the user and proceed unless they object.

## Step 2 — Select a test

| User hypothesis shape | Variables | Default test |
|---|---|---|
| Group A mean ≠ Group B mean | 1 numeric + 1 binary categorical | Welch's t-test (unequal var) or Mann-Whitney if non-normal |
| Difference across 3+ groups | 1 numeric + 1 categorical | One-way ANOVA or Kruskal-Wallis |
| Association between two categoricals | 2 categoricals | Chi-square (or Fisher's exact if small cells) |
| Correlation ≠ 0 | 2 numerics | Pearson (linear) or Spearman (monotonic) |
| Proportion differs from value | 1 binary | One-sample proportion z-test |
| Paired before/after | 1 numeric, paired | Paired t-test or Wilcoxon signed-rank |
| Time trend | 1 numeric + time | Mann-Kendall or regression slope test |

Check assumptions (normality via Shapiro-Wilk for small n or visual for large n; equal variance via Levene's) and fall back to the non-parametric counterpart when they fail.

## Step 3 — Execute

Recommended: `uv run --with pandas --with scipy --with statsmodels python -c '...'`.

Report:
- Sample size(s)
- Effect size (Cohen's d, r, Cramér's V, odds ratio — whichever fits)
- Test statistic and p-value
- 95% confidence interval for the effect

## Step 4 — Verdict

Classify as one of:

- **Supports** — p  0.05" with "no effect" — distinguish "evidence of no effect" (tight CI around zero) from "no evidence of effect" (wide CI).

## Output

Write `-hypothesis-.md`:

1. The hypothesis as stated by the user, verbatim.
2. Formalised H₀ / H₁.
3. Test chosen and why (including assumption checks).
4. Results table.
5. **Verdict** in bold: supports / refutes / inconclusive, with a plain-English explanation.
6. Caveats (confounders, selection effects, multiple-comparisons risk if this is one of many tests).

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [danielrosehill](https://github.com/danielrosehill)
- **Source:** [danielrosehill/Claude-Data-Analyst-plugin](https://github.com/danielrosehill/Claude-Data-Analyst-plugin)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-danielrosehill-claude-data-analyst-plugin-hypothesis-testing
- Seller: https://agentstack.voostack.com/s/danielrosehill
- Browse the marketplace: https://agentstack.voostack.com/browse

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