Here are 100 people picked randomly from the population on planet earth:

A 30-34 year old male in ChinaA 35-39 year old female in TurkeyA 20-24 year old male in BrazilA 25-29 year old male in ChinaA 50-54 year old male in ChinaA 25-29 year old female in EthiopiaA 25-29 year old female in IndonesiaA 40-44 year old male in BrazilA 30-34 year old female in MadagascarA 5-9 year old female in IndiaA 60-64 year old female in SpainA 15-19 year old male in IndiaA 75-79 year old male in ThailandA 55-59 year old male in ChinaA 10-14 year old female in IndiaA 40-44 year old male in IndonesiaA 70-74 year old female in ChinaA 55-59 year old female in IndiaA 50-54 year old male in ChinaA 40-44 year old male in ChinaA 30-34 year old male in IndiaA 50-54 year old female in ChinaA 10-14 year old male in PakistanA 30-34 year old male in United Republic of TanzaniaA 30-34 year old female in IndonesiaA 55-59 year old female in IndiaA 65-69 year old female in IndiaA 0-4 year old male in MozambiqueA 30-34 year old female in GermanyA 40-44 year old male in BangladeshA 35-39 year old male in SpainA 40-44 year old female in ChinaA 5-9 year old male in MexicoA 55-59 year old male in ChinaA 15-19 year old male in South AfricaA 15-19 year old female in ChinaA 50-54 year old male in ChinaA 35-39 year old male in IndiaA 40-44 year old male in IndiaA 35-39 year old female in IndiaA 20-24 year old male in South AfricaA 45-49 year old female in ChinaA 5-9 year old male in United KingdomA 75-79 year old female in United States of AmericaA 30-34 year old male in EthiopiaA 20-24 year old female in Burkina FasoA 40-44 year old female in IndiaA 0-4 year old female in ItalyA 30-34 year old female in ChadA 5-9 year old male in ChinaA 45-49 year old female in ChinaA 30-34 year old male in IndiaA 0-4 year old male in Democratic Republic of the CongoA 70-74 year old female in MadagascarA 20-24 year old male in BrazilA 30-34 year old male in MozambiqueA 10-14 year old male in PakistanA 30-34 year old female in Czech RepublicA 10-14 year old female in NigeriaA 35-39 year old male in Saudi ArabiaA 25-29 year old male in CambodiaA 20-24 year old male in ChinaA 35-39 year old male in SudanA 0-4 year old male in ChinaA 30-34 year old male in BangladeshA 40-44 year old male in ChinaA 35-39 year old female in Republic of KoreaA 0-4 year old female in CameroonA 30-34 year old male in IndiaA 50-54 year old male in ChadA 40-44 year old female in United States of AmericaA 30-34 year old female in BangladeshA 55-59 year old female in JapanA 35-39 year old male in SwedenA 15-19 year old female in Republic of KoreaA 25-29 year old female in ChinaA 45-49 year old female in IndiaA 35-39 year old male in IndiaA 10-14 year old male in IndiaA 25-29 year old female in ChinaA 95-100 year old female in United States of AmericaA 40-44 year old male in Other non-specified areas*A 50-54 year old female in IndiaA 0-4 year old male in ChinaA 45-49 year old female in ChinaA 55-59 year old female in South AfricaA 50-54 year old male in PhilippinesA 35-39 year old male in Venezuela (Bolivarian Republic of)A 60-64 year old female in MyanmarA 0-4 year old female in EgyptA 80-84 year old female in United States of AmericaA 50-54 year old female in Papua New GuineaA 30-34 year old female in New ZealandA 15-19 year old male in IndiaA 40-44 year old female in GermanyA 25-29 year old female in IndiaA 50-54 year old female in TurkeyA 15-19 year old female in ChinaA 15-19 year old male in IndiaA 5-9 year old female in India

Does anything stand out? Any surprises? Is your demographic group represented? How many people do you know that fall into ANY of these groups? (My answer is 4!)

As you may have noticed contemplating these questions, random samples can provide a perspective that we identify with on a somewhat more emotional level than raw statistics.

But getting a truly random sample is often harder than it may seem at first, as demonstrated in a previous post about random places on Earth. The list above is the result of a similar experiment with people.

As we know there is no global population register. That may in fact be just as well given the occasional political craziness that we humans find ourselves in, but it does prevent us from getting down in an experiment like this one. We can however get down to demographic groups like the ones listed above.

The United Nations Department of Economic and Social Affairs’ Population Division⚠ has exact and/or very well estimated demographic data for every country broken down by sex and 5-year age groups. For each of those demographic groups they have the number of people (reported in thousands of people, but with up to 3 decimals, so the estimates are essentially down to an individual person).

Using this data, we can “line up” the people on Earth for random picking. So the “first” person in that line would be a 0–4 year old boy in Afghanistan (there are over 2.5 million of them) and the “last” person would be a 100+ year old woman in Zimbabwe (there were an estimated 67 of them).

The latest data is for 2015 and reports a world population of 7,348,416,351. So now that we have everybody lined up, all we have to do to pick a random person is to randomly pick a number between 1 and 7,348,416,351 and we will have a realistic country of residence, sex and age group for our pick.

Repeat this 100 times and you get to a list like the one above. How many do you need until you find “someone like you”?

You can download the Excel-file I created and try it on your own. Improvements and suggestions welcomed.

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