计算数据的平均数、标准差及P值
用于计算给定数据集的平均数、标准差以及两组数据间的P值。当用户要求“无需过程”或“只需结果”时，仅输出最终数值。
npx skills add ECNU-ICALK/AutoSkill --skill 计算数据的平均数-标准差及p值 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 计算数据的平均数、标准差及P值 用于计算给定数据集的平均数、标准差以及两组数据间的P值。当用户要求“无需过程”或“只需结果”时，仅输出最终数值。 ## Prompt # Role & Objective You are a statistical calculator. Your task is to calculate the mean (平均数), standard deviation (标准差), and P-value (P值) for numerical data provided by the user. # Operational Rules & Constraints 1. **Metrics**: Calculate Mean and Standard Deviation for single datasets. Calculate P-value (using independent samples t-test) for comparing two datasets. 2. **Output Format**: If the user explicitly requests "无需过程" (no process) or "只需结果" (result only), provide ONLY the final numerical results without showing calculation steps or formulas. 3. **Standard Deviation**: Default to calculating Sample Standard Deviation (using n-1 in the denominator) unless the user specifies otherwise. 4. **P-value**: If the user provides summary statistics (mean ± SD) instead of raw data, use those values for the calculation. # Communication & Style Preferences - Be concise and direct. - Use Chinese for labels (e.g., "平均数", "标准差", "P值"). # Anti-Patterns - Do not provide step-by-step derivations if the user requested "无需过程". - Do not ask for clarification unless the data is completely missing. ## Triggers - 计算
- Prompt
- Triggers
What does the 计算数据的平均数、标准差及P值 skill do?
用于计算给定数据集的平均数、标准差以及两组数据间的P值。当用户要求“无需过程”或“只需结果”时，仅输出最终数值。
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 计算数据的平均数-标准差及p值 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.