cc-statistics
Use when defining n, choosing statistical tests, correcting for multiple comparisons, and reporting error bars for a Cancer Cell (Cell Press) manuscript. Focuses on biological statistics and avoiding pseudo-replication; it does not design experiments or build figures.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cc-statistics --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.
# Biological Statistics (cc-statistics) ## When to trigger - `n` is ambiguous, or you suspect pseudo-replication - Unsure which test fits the data and design - Many comparisons without multiplicity correction - Error bars / variability are unlabeled in figures or legends ## Defining `n` (the core issue) - `n` = number of **independent biological replicates** (separate mice, independent cultures/passages, distinct patients). - Technical replicates (duplicate wells, repeat reads) describe measurement precision and **do not** count toward `n`. - State `n` for **every** panel in the legend, with what one unit is ("n = 5 mice per group", "n = 3 independent experiments"). - Pooling cells from many wells of one experiment and calling it n=many is **pseudo-replication** — a classic Cancer Cell reviewer catch. ## Choosing the test | Design | Typical test | |--------|--------------| | Two groups, continuous, ~normal | Unpaired t-test (Welch if unequal variance) | | Two paired conditions | Paired t-test | | Two groups, non-normal / small n | Mann-Whitney U | | >2 groups, one factor | One-way ANOVA + post-hoc (Tukey/Dunnett) | | Two factors (e.g., genotype × treatment) | Two-way ANOVA + correc
- When to trigger
- Defining n (the core issue)
- Choosing the test
- Multiple comparisons
- Error bars and reporting
- Checklist
- Anti-patterns
- Statistics pass for Cancer Cell
- Output format
What does the cc-statistics skill do?
Use when defining n, choosing statistical tests, correcting for multiple comparisons, and reporting error bars for a Cancer Cell (Cell Press) manuscript. Focuses on biological statistics and avoiding pseudo-replication; it does not design experiments or build figures.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cc-statistics --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 brycewang-stanford/Awesome-Journal-Skills, a repository with 909 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.