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Performs and explains basic statistical calculations — percentages, percentage changes, per-capita rates, averages, medians, and ratios — from data you provide, showing the working so you can verify it and use the figures confidently in a story.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generates the complete set of metadata fields — tags, categories, keywords, slug, and summary — needed to publish a piece of content in a content management system, ready to copy and paste into each field.
Takes a finished piece of content and produces a complete, archive-ready metadata record — including descriptive tags, subject classifications, rights notes, and an archival summary — for entry into a content management or digital archive system.
Drafts a GDPR compliance note for a specific piece of journalistic content or data collection activity — documenting the lawful basis for processing personal data, what data is held, how long it is retained, and who has access.
Reviews the details of a specific image and flags potential rights clearance issues before publication, identifying which permissions you likely need and which questions to bring to your legal or picture desk.
Reviews a story brief, draft article, or broadcast script and flags potential legal risks — including defamation, privacy, contempt of court, and data protection — so you know what to check before publication.
Drafts a formal, professional request letter to a music rights holder asking for permission to use a track in a specific media production under defined terms.
| name | basic-statistics-calculator |
| description | Performs and explains basic statistical calculations — percentages, percentage changes, per-capita rates, averages, medians, and ratios — from data you provide, showing the working so you can verify it and use the figures confidently in a story. |
| status | stable |
| category | data-journalism |
| subcategory | analysis |
| version | 1 |
| eval_score | 4.39 |
| tags | ["data-journalism","statistics","calculations","analysis","numbers","percentages","averages"] |
Performs and explains basic statistical calculations — percentages, percentage changes, per-capita rates, averages, medians, and ratios — from data you provide, showing the working so you can verify it and use the figures confidently in a story.
Required: The raw numbers or data points; the calculation you need (percentage, percentage change, per-capita rate, average, median, ratio, or "tell me what is most useful for this story"); the context — what these numbers represent and where they come from.
Optional: The population or base figure for per-capita calculations; the time period the data covers; the comparison you want to make (year-over-year, city-to-city, before-and-after); the audience level (general public, specialist readers, other journalists); how you plan to use the result (headline figure, in-text comparison, chart label).
Confirms the inputs and the ask. Restates the numbers provided, what they represent, and what calculation is being requested. This step catches misunderstandings before any math is done — if the user provided annual figures but asked for a monthly rate, that discrepancy is flagged here.
Performs the calculation with full working shown. Every step of the arithmetic is written out in plain language and with the formula. Nothing is hidden in a black box. The journalist can follow each step, check it against the source data, and verify the result independently. Rounding decisions are stated explicitly (e.g., "rounded to one decimal place").
Interprets the result in plain English. After the math, writes one sentence explaining what the number means in the context of the story. This is the sentence a journalist could use in their article — clear, accurate, and free of statistical jargon. If the result is surprising or potentially misleading without context, that is flagged.
Flags caveats and common pitfalls. Notes any issues with the calculation: small sample sizes that make percentages misleading, base-rate effects that make percentage changes deceptive, denominators that changed between periods (making direct comparison unreliable), or the difference between correlation and causation if the user is implying a causal relationship.
Suggests a second calculation when relevant. If a single figure tells an incomplete story — for example, a percentage change without the absolute numbers, or an average that hides a skewed distribution — suggests the additional calculation and explains why it matters for editorial accuracy.
A structured calculation report of 200-400 words. Opens with "Inputs" (restating the data), then "Calculation" (step-by-step working with formula), then "Result" (the final figure), then "In Plain English" (one sentence for the story), then "Caveats" (any statistical warnings). If a second calculation is suggested, it follows the same structure. Tone is precise and educational — written for a journalist who is competent but not a statistician.
**Inputs**
[Restated data and what was asked]
**Calculation**
[Step-by-step working with formula]
**Result:** [Final figure]
**In Plain English:** [One usable sentence for the story]
**Caveats**
- [Any statistical warnings or context needed]
**Additional Calculation (if relevant)**
[Same structure]
Data: In 2019, the city recorded 340 reported burglaries. In 2024, the city recorded 285 reported burglaries. The city's population was 210,000 in 2019 and 225,000 in 2024.
Calculation needed: Percentage change in burglaries, and per-capita burglary rate for both years, so I can write accurately about whether burglary has actually declined.
Context: I am writing a local news story about crime trends. The police chief has claimed that "burglary is down significantly."
Inputs
Calculation 1: Percentage Change in Reported Burglaries
Formula: ((New Value - Old Value) / Old Value) x 100
((285 - 340) / 340) x 100 = (-55 / 340) x 100 = -16.2%
Result: Reported burglaries fell 16.2% between 2019 and 2024.
In Plain English: The city recorded 16% fewer burglaries in 2024 than in 2019, dropping from 340 to 285 reported incidents.
Calculation 2: Per-Capita Burglary Rate (per 10,000 residents)
Formula: (Number of burglaries / Population) x 10,000
2019: (340 / 210,000) x 10,000 = 16.2 burglaries per 10,000 residents 2024: (285 / 225,000) x 10,000 = 12.7 burglaries per 10,000 residents
Percentage change in per-capita rate: ((12.7 - 16.2) / 16.2) x 100 = -21.6%
Result: The per-capita burglary rate fell from 16.2 to 12.7 per 10,000 residents — a 21.6% decline.
In Plain English: After adjusting for population growth, the burglary rate fell 22% over five years — from roughly 16 burglaries per 10,000 residents to roughly 13.
Caveats