{
  "id": "1995-may-slice-percents-right",
  "slug": "1995-may-slice-percents-right",
  "url": "https://dwillis.github.io/uplink/article/1995-may-slice-percents-right.html",
  "year": 1995,
  "month": "May",
  "monthNum": 5,
  "headline": "Slice percents right",
  "kicker": "Yogi Berra might say 90 percent of journalism is half mental",
  "author_name": "Jennifer LaFleur",
  "author_title": "Staff",
  "affiliation": "NICAR",
  "summary": "This article explains three essential mathematical formulas for computer-assisted reporting in journalism: percent change, percent of total, and per capita, with practical examples to help reporters analyze data effectively.",
  "keywords": [
    "formulas",
    "reporting",
    "data"
  ],
  "topics": [
    "Investigative Methods",
    "Data & Databases"
  ],
  "technologies": [
    "spreadsheet"
  ],
  "full_text": "So you went into journalism to avoid math? For the more nerdy, mathematical formulas may come as naturally as slipping on a pocket protector each morning; however, to those just starting in computer-assisted reporting, math can be intimidating.\n\nI'm not suggesting that to do computer-assisted reporting you have to have an immediate grasp of differential equations, but whether you're looking at hard copy reports from a government agency or analyzing data in a spreadsheet, you should be familiar with three key formulas: percent change, percent of total and per capita.\n\nPercent of total\n\nThis one is easy to get turned around. The rule is: the amount divided by the total (amount/total). For example, if Bob owns 10 animals and two of those animals are cats, 2 divided by 10 (2/10) or 20 percent of his animals are cats.\n\nPercent change\n\nYou're dealing with two years' worth of data and want to figure percent change from one year to the next. Take the difference of the two years divided by the amount from the earlier year. Say we're looking at 1993-1994 data. The difference: 2,567 - 2,345 = 222. Now: 222/2,345 = 0.09.\n\nPer capita\n\nLooking at occurrences by city or county or state can be interesting. But remember to keep things on common ground. You can't compare raw numbers if the \"bases\" are different. That means if I'm looking at the number of murders by city in the United States, Los Angeles and New York probably will come out on top, but only because they have more people. A more useful measure would be per capita murders. In this case, per capita murders would be the number of murders divided by population.\n\nSometimes these measures will be adjusted a little if the number of occurrences is low. Crime statistics, for example often are reported per 100,000 or per 10,000 people. These measures are used because (hopefully) the number of murders in a city is fairly low compared to the number of people. The per capita measure might be 0.0005 - yikes! By looking at the figure per 100,000 people, it becomes easier to read: 50 murders per 100,000 people.\n\nWhen you're trying to figure if persons per household is households divided by population or population divided by households. Do one simple thing: turn your per into a division sign. This means that persons PER households becomes persons/households or population/households. If that doesn't work, trying narrowing the field to a few items: for example if I have two houses and 10 people, how many persons per household is that? Of course, it's five a house.\n\nJennifer LaFleur can be reached at (314) 882-9491, or send e-mail to jenster@aol.com",
  "provenance": {
    "extracted_by": "anthropic/claude-sonnet-4-6",
    "extracted_at": "2026-07-05",
    "verified": true
  },
  "similar": [
    {
      "slug": "2006-may-june-excel-and-vb-help-crack-school-finances",
      "score": 0.194
    },
    {
      "slug": "1997-decemberjanuary-math-for-every-reporter",
      "score": 0.18
    },
    {
      "slug": "1996-october-math-for-journalists",
      "score": 0.156
    },
    {
      "slug": "1994-december-uplink-update",
      "score": 0.14
    },
    {
      "slug": "2001-julyaugust-teaching-car",
      "score": 0.138
    }
  ],
  "html_url": "https://dwillis.github.io/uplink/article/1995-may-slice-percents-right.html",
  "json_url": "https://dwillis.github.io/uplink/article/1995-may-slice-percents-right.json"
}