A clever way to estimate enormous numbers - Michael Mitchell

1,036,610 views ใƒป 2012-09-12

TED-Ed


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค.

๋ฒˆ์—ญ: Woo Hwang ๊ฒ€ํ† : K Bang
00:15
Whether you like it or not, we use numbers every day.
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์—ฌ๋Ÿฌ๋ถ„๋“ค์ด ์ข‹๋“  ์‹ซ๋“ , ์šฐ๋ฆฌ๋Š” ๋งค์ผ ์ˆซ์ž๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.
00:18
Some numbers, such as the speed of sound,
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์˜ˆ๋ฅผ๋“ค์–ด ์†Œ๋ฆฌ์˜ ์†๋„์™€ ๊ฐ™์€ ์ˆซ์ž๋“ค์€ ์ž‘๊ณ  ์ฒ˜๋ฆฌํ•˜๊ธฐ ์‰ฝ์Šต๋‹ˆ๋‹ค.
00:20
are small and easy to work with.
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00:22
Other numbers, such as the speed of light,
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๋น›์˜ ์†๋„์™€ ๊ฐ™์€ ์ˆซ์ž๋“ค์€ ํ›จ์”ฌ ํฌ๊ณ  ๋‹ค๋ฃจ๊ธฐ ๊นŒ๋‹ค๋กญ์Šต๋‹ˆ๋‹ค.
00:24
are much larger and cumbersome to work with.
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00:26
We can use scientific notation to express these large numbers
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์‚ฌ๋žŒ๋“ค์€ ์ด๋ ‡๊ฒŒ ํฐ ์ˆซ์ž๋“ค์„ ๋‹ค๋ฃจ๊ธฐ ์‰ฌ์šด ํ˜•์‹์œผ๋กœ ํ‘œํ˜„ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๊ณผํ•™์  ํ‘œ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค.
00:29
in a much more manageable format.
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00:31
So we can write 299,792,458 meters per second
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๊ทธ๋ž˜์„œ 299,792,458 ๋ฏธํ„ฐ๋Š” ์ดˆ๋‹น 3.0 ๊ณฑํ•˜๊ธฐ 10์˜ 8์ œ๊ณฑ ๋ฏธํ„ฐ๋ผ๊ณ  ์”๋‹ˆ๋‹ค.
00:37
as 3.0 times 10 to the eighth meters per second.
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00:41
Correct scientific notation
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์˜ฌ๋ฐ”๋ฅธ ๊ณผํ•™์  ํ‘œ๊ธฐ๋ฒ•์—์„œ๋Š” ์ฒซ๋ฒˆ์งธ ํ•ญ์˜ ์ˆซ์ž๊ฐ€ 1๋ณด๋‹ค๋Š” ํฌ๊ณ  10 ๋ณด๋‹ค ์ž‘์€ ์ˆซ์ž๋ฅผ ์“ฐ๋„๋ก ํ•ฉ๋‹ˆ๋‹ค,
00:43
requires that the first term range in value
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00:45
so that it is greater than one but less than 10,
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๊ทธ๋ฆฌ๊ณ  ๋‘๋ฒˆ์งธ ํ•ญ์€ 10์˜ ์ œ๊ณฑ์ˆ˜, ์ฆ‰ ํฌ๊ธฐ์˜ ์ •๋„์ธ๋ฐ, ์ด๊ฒƒ์„ ์ฒซ๋ฒˆ์งธ ํ•ญ์— ๊ณฑํ•ด ์ž๋ฆฌ์ˆ˜๋กœ ํ‘œํ˜„ํ•ฉ๋‹ˆ๋‹ค.
00:47
and the second term represents the power of 10 or order of magnitude
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00:50
by which we multiply the first term.
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์ •ํ™•ํ•œ ๊ฐ’์ด๋‚˜ ์ˆซ์ž๊ฐ€ ํ•„์š”ํ•˜์ง€ ์•Š์„ ๋•Œ๋Š” 10์˜ ์ œ๊ณฑ์ˆ˜๋ฅผ ํ†ตํ•ด ํฌ๊ธฐ๋ฅผ ๋น ๋ฅด๊ฒŒ ๊ฐ€๋Š ํ•ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
00:53
We can use the power of 10 as a tool in making quick estimations
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00:56
when we do not need or care for the exact value of a number.
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00:59
For example, the diameter of an atom
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์˜ˆ๋ฅผ ๋“ค์–ด, ์›์ž์˜ ์ง€๋ฆ„์€ ๋Œ€๋žต 10์˜ ๋งˆ์ด๋„ˆ์Šค 12์ œ๊ณฑ ๋ฏธํ„ฐ์ž…๋‹ˆ๋‹ค.
01:01
is approximately 10 to the power of negative 12 meters.
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01:04
The height of a tree is approximately 10 to the power of one meter.
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๋‚˜๋ฌด์˜ ๋†’์ด๋Š” ์•ฝ 10์˜ 1์ œ๊ณฑ ๋ฏธํ„ฐ ์ •๋„์ž…๋‹ˆ๋‹ค.
01:07
The diameter of the Earth is approximately 10 to the power of seven meters.
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๊ทธ๋ฆฌ๊ณ  ์ง€๊ตฌ์˜ ์ง€๋ฆ„์€ ์•ฝ 10์˜ 7์ œ๊ณฑ ๋ฏธํ„ฐ์ •๋„์ž…๋‹ˆ๋‹ค.
์ˆซ์ž๋ฅผ ์ธก์ •ํ•ด๋ณด๋Š” ๋„๊ตฌ๋กœ์จ 10์˜ ์ œ๊ณฑ์ˆ˜๋Š” ์–ธ์ œ๋‚˜ ํŽธ๋ฆฌํ•ฉ๋‹ˆ๋‹ค,
01:11
The ability to use the power of 10 as an estimation tool
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01:13
can come in handy every now and again,
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01:15
like when you're trying to guess the number of M&M's in a jar,
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๋งˆ์น˜ ์—ฌ๋Ÿฌ๋ถ„๋“ค์ด ๋ณ‘์†์— ๋“ค์–ด์žˆ๋Š” ์ดˆ์ฝœ๋ › ๊ฐฏ์ˆ˜๋ฅผ ๊ฐ€๋Š ํ•ด ๋ณผ ๋•Œ ์ฒ˜๋Ÿผ ๋ง์ด์ฃ .
์ด๊ฒƒ์€ ์ˆ˜ํ•™๊ณผ ๊ณผํ•™์—์„œ ํ•„์š”๋กœ ํ•˜๋Š” ๋ฐฉ๋ฒ•์ด๊ณ , ํŠนํžˆ ํŽ˜๋ฅด๋ฏธ(Fermi)์˜ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃฐ ๋•Œ๋Š” ๋”์šฑ ๊ทธ๋ ‡์Šต๋‹ˆ๋‹ค.
01:18
but is also an essential skill in math and science,
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01:21
especially when dealing with what are known as Fermi problems.
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ํŽ˜๋ฅด๋ฏธ์˜ ๋ฌธ์ œ๋Š” ํฌ๊ธฐ ์ถ”์ •์„ ๋น ๋ฅด๊ฒŒ ํ•˜๊ธฐ๋กœ ์œ ๋ช…ํ•œ ์ดํƒœ๋ฆฌ ๋ฌผ๋ฆฌํ•™์ž ์—”๋ฆฌ์ฝ” ํŽ˜๋ฅด๋ฏธ(Enrico Fermi)์˜ ์ด๋ฆ„์„ ๋”ฐ์„œ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค,
01:24
Fermi problems are named after the physicist Enrico Fermi,
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01:26
who's famous for making rapid order-of-magnitude estimations,
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์ฆ‰, ๋Œ€๋žต ์ ์€ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฐ€์ง€๊ณ  ๋นจ๋ฆฌ ์ถ”์ •ํ•ด๋ณด๋Š” ๋ฐฉ๋ฒ•์ด๋ผ๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
01:29
or rapid estimations, with seemingly little available data.
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01:32
Fermi worked on the Manhattan Project in developing the atomic bomb,
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ํŽ˜๋ฅด๋ฏธ๋Š” ์›์žํญํƒ„์„ ๊ฐœ๋ฐœํ•œ ๋งจํ•˜ํƒ„ ํ”„๋กœ์ ํŠธ(Manhattan Project)์—์„œ ์—ฐ๊ตฌํ–ˆ์Šต๋‹ˆ๋‹ค.
01:35
and when it was tested at the Trinity site in 1945,
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๊ทธ๋ฆฌ๊ณ  1945๋…„์— ํŠธ๋ฆฌ๋‹ˆํ‹ฐ(Trinity)์—์„œ ์‹คํ—˜์„ ํ•  ๋•Œ, ํŽ˜๋ฅด๋ฏธ๋Š” ํญ๋ฐœ ๋™์•ˆ ๋ช‡ ์žฅ์˜ ์ข…์ด๋ฅผ ๋–จ์–ด๋œจ๋ ธ์Šต๋‹ˆ๋‹ค,
01:38
Fermi dropped a few pieces of paper during the blast
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๊ทธ๋ฆฌ๊ณ  ๊ทธ ์ข…์ด๋“ค์ด ๋‚ ์•„๊ฐ€๋Š” ๊ฑฐ๋ฆฌ๋ฅผ ํ†ตํ•ด์„œ ํญ๋ฐœ์˜ ๊ฐ•๋„๋ฅผ
01:41
and used the distance they traveled backwards as they fell
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01:43
to estimate the strength of the explosion as 10 kilotons of TNT,
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TNT ํญํƒ„ 10ํ‚ฌ๋กœํ†ค์œผ๋กœ ์ถ”์ •ํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์‹ค์ œ๋กœ๋Š” 20ํ‚ฌ๋กœํ†ค ์ •๋„์˜ ํฌ๊ธฐ์˜€์ง€์š”.
01:47
which is on the same order of magnitude as the actual value of 20 kilotons.
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01:51
One example of the classic Fermi estimation problems
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ํŽ˜๋ฅด๋ฏธ ์ถ”์ •์˜ ๋Œ€ํ‘œ์ ์ธ ์˜ˆ๋Š” ๋ฏธ๊ตญ ์‹œ์นด๊ณ ์— ์–ผ๋งˆ๋‚˜ ๋งŽ์€ ํ”ผ์•„๋…ธ ์กฐ์œจ์‚ฌ๊ฐ€ ์žˆ๋Š”์ง€ ๊ณ„์‚ฐํ•ด๋ณด๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
01:54
is to determine how many piano tuners there are
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01:56
in the city of Chicago, Illinois.
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01:58
At first, there seem to be so many unknowns
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์šฐ์„ , ํ’€๋ฆฌ์ง€ ์•Š์€ ๋„ˆ๋ฌด๋‚˜๋„ ๋งŽ์€ ๋ฏธ์ง€์ˆ˜๊ฐ€ ์žˆ์„ ๊ฒƒ ๊ฐ™์Šต๋‹ˆ๋‹ค.
02:01
that the problem appears to be unsolvable.
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๊ทธ ๋ฌธ์ œ๋Š” ์ •ํ™•ํ•œ ๋‹ต์„ ์•Œ ํ•„์š”๋Š” ์—†์„ ๋•Œ, 10์˜ ์ œ๊ณฑ์ˆ˜๋ฅผ ์‘์šฉํ•œ ์ข‹์€ ์˜ˆ์ž…๋‹ˆ๋‹ค.
02:03
That is the perfect application for a power-of-10 estimation,
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02:06
as we don't need an exact answer -
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02:07
an estimation will work.
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์ถ”์ •์€ ์ž˜ ๋งž์Šต๋‹ˆ๋‹ค.
02:09
We can start by determining how many people live in the city of Chicago.
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๋จผ์ € ์‹œ์นด๊ณ ์˜ ์ธ๊ตฌ์ˆ˜๋ฅผ ์กฐ์‚ฌํ•ด ๋ด…๋‹ˆ๋‹ค.
02:12
We know that it is a large city,
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์šฐ๋ฆฌ๋Š” ์‹œ์นด๊ณ ๊ฐ€ ๋Œ€๋„์‹œ๋ผ๋Š” ๊ฒƒ์„ ์•Œ๊ณ  ์žˆ์ง€๋งŒ, ์ •ํ™•ํ•˜๊ฒŒ ๋ช‡ ๋ช…์ด ์‚ด๊ณ  ์žˆ๋Š”์ง€๋Š” ๋ช…ํ™•ํ•˜๊ฒŒ ๋ชจ๋ฆ…๋‹ˆ๋‹ค.
02:14
but we may be unsure about exactly how many people live in the city.
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02:17
Are the one million people? Five million people?
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3๋ฐฑ๋งŒ๋ช… ์ผ๊นŒ์š”? 5๋ฐฑ๋งŒ๋ช… ์ •๋„ ์žˆ์„๊นŒ์š”?
02:20
This is the point in the problem
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๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ์ด๋Ÿฐ ๋ถˆํ™•์‹ค์„ฑ์— ๋ถˆํŽธํ•ดํ•˜๋Š” ๊ฒƒ์ด ์ด ๋ฌธ์ œ์˜ ์š”์ ์ž…๋‹ˆ๋‹ค,
02:22
where many people become frustrated with the uncertainty,
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ํ•˜์ง€๋งŒ ์šฐ๋ฆฌ๋Š” 10์˜ ์ œ๊ณฑ์ˆ˜๋ฅผ ํ†ตํ•ด์„œ ์‰ฝ๊ฒŒ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:25
but we can easily get through this by using the power of 10.
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์‹œ์นด๊ณ ์˜ ์ธ๊ตฌ ํฌ๊ธฐ๋ฅผ 10์˜ 6์ œ๊ณฑ ํฌ๊ธฐ๋กœ ์ถ”์ •ํ•ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:28
We can estimate the magnitude of the population of Chicago
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02:30
as 10 to the power of six.
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02:32
While this doesn't tell us exactly how many people live there,
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์ด ์ˆซ์ž๊ฐ€ ์ •ํ™•ํ•œ ์ธ๊ตฌ์ˆ˜๋Š” ์•„๋‹ˆ์ง€๋งŒ,
02:35
it serves an accurate estimation for the actual population
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์‹ค์ œ ์ธ๊ตฌ๊ฐ€ ๋Œ€๋žต 3๋ฐฑ๋งŒ๋ช…์ด ์กฐ๊ธˆ ์•ˆ๋˜๋Š” ์‹ค์ œ ์ธ๊ตฌ์— ๋Œ€ํ•œ ์ถ”์ •์น˜๋Š” ๋ฉ๋‹ˆ๋‹ค.
02:38
of just under three million people.
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02:40
So if there are approximately 10 to the sixth people in Chicago,
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๊ทธ๋ž˜์„œ ์‹œ์นด๊ณ ์— 10์˜ 6์ œ๊ณฑ ์ •๋„์˜ ์ธ๊ตฌ๊ฐ€ ์žˆ๋‹ค๋ฉด ํ”ผ์•„๋…ธ๋Š” ๋ช‡ ๋Œ€๊ฐ€ ์žˆ์„๊นŒ์š”?
02:43
how many pianos are there?
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02:44
If we want to continue dealing with orders of magnitude,
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์šฐ๋ฆฌ๊ฐ€ ๊ณ„์†ํ•ด์„œ ํฌ๊ธฐ๋กœ ์ด์•ผ๊ธฐ๋ฅผ ํ•œ๋‹ค๋ฉด,
02:47
we can either say that one out of 10
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10๋ช…์ค‘์— 1๋ช… ๋˜๋Š” 100๋ช…์ค‘์— 1๋ช…์ด ํ”ผ์•„๋…ธ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๊ณ  ๋งํ•  ์ˆ˜ ์žˆ๊ฒ ์ฃ .
02:49
or one out of one hundred people own a piano.
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02:51
Given that our estimate of the population includes children and adults,
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์ธ๊ตฌ์ˆ˜์— ์–ด๋ฆฐ์ด์™€ ์„ฑ์ธ์ด ํฌํ•จ๋˜์—ˆ๋‹ค๋ฉด,
02:55
we'll go with the latter estimate,
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์‹œ์นด๊ณ ์— ์•ฝ 10์˜ 4์ œ๊ณฑ๊ฐœ, ์ฆ‰ 10,000๋Œ€ ์ •๋„์˜ ํ”ผ์•„๋…ธ๊ฐ€ ์žˆ๋‹ค๊ณ  ์ถ”์ •ํ•ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:57
which estimates that there are approximately 10 to the fourth,
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03:00
or 10,000 pianos, in Chicago.
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์ด๋ ‡๊ฒŒ ๋งŽ์€ ํ”ผ์•„๋…ธ๊ฐ€ ์žˆ๋‹ค๋ฉด, ํ”ผ์•„๋…ธ ์กฐ์œจ์‚ฌ๋Š” ๋ช‡ ๋ช…์ด๋‚˜ ์žˆ์„๊นŒ์š”?
03:02
With this many pianos, how many piano tuners are there?
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03:05
We could begin the process of thinking about how often the pianos are tuned,
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ํ”ผ์•„๋…ธ๋ฅผ ์–ผ๋งˆ๋‚˜ ์ž์ฃผ ์กฐ์œจํ•˜๋Š”์ง€๋ถ€ํ„ฐ ์ƒ๊ฐํ•ด๋ณด๊ฑฐ๋‚˜,
ํ•˜๋ฃจ์— ์–ผ๋งˆ๋‚˜ ๋งŽ์€ ํ”ผ์•„๋…ธ๊ฐ€ ์กฐ์œจ๋˜๋Š”์ง€, ๋˜๋Š” ์กฐ์œจ์‚ฌ๊ฐ€ ๋ช‡ ์ผ์„ ์ผํ•˜๋Š”์ง€ ์ƒ๊ฐํ•ด๋ณด์ฃ ,
03:09
how many pianos are tuned in one day,
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03:11
or how many days a piano tuner works,
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03:13
but that's not the point of rapid estimation.
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ํ•˜์ง€๋งŒ ๊ทธ๊ฒƒ์ด ๋น ๋ฅธ ์ถ”์ •์˜ ์š”์ ์€ ์•„๋‹™๋‹ˆ๋‹ค.
03:15
We instead think in orders of magnitude,
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195539
1929
ํฌ๊ธฐ๋ฅผ ์ƒ๊ฐํ•˜์ง€ ๋ง๊ณ , ์กฐ์œจ์‚ฌ๊ฐ€ 1๋…„์— 10์˜ 2์ œ๊ณฑ๊ฐœ ์ •๋„์˜ ํ”ผ์•„๋…ธ๋ฅผ ์กฐ์œจํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋ฉด,
03:17
and say that a piano tuner tunes roughly 10 to the second pianos in a given year,
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03:21
which is approximately a few hundred pianos.
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201500
2151
๊ทธ ์ˆซ์ž๋Š” ์•ฝ ๋ช‡ ๋ฐฑ๊ฐœ์ •๋„ ์ž…๋‹ˆ๋‹ค.
03:23
Given our previous estimate of 10 to the fourth pianos in Chicago,
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203675
3285
์•ž์˜ ์ถ”์ •์—์„œ 10์˜ 4์ œ๊ณฑ๊ฐœ์˜ ํ”ผ์•„๋…ธ๊ฐ€ ์‹œ์นด๊ณ ์— ์žˆ๋‹ค๊ณ  ํ–ˆ์Šต๋‹ˆ๋‹ค,
03:26
and the estimate that each piano tuner can tune 10 to the second pianos each year,
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4099
๊ทธ๋ฆฌ๊ณ  ์กฐ์œจ์‚ฌ๊ฐ€ ๋งค๋…„ 10์˜ 2์ œ๊ณฑ๋ฒˆ ํ”ผ์•„๋…ธ๋ฅผ ์กฐ์œจํ•œ๋‹ค๊ณ  ํ–ˆ์ฃ ,
๊ทธ๋Ÿผ ์‹œ์นด๊ณ ์—๋Š” ์•ฝ 10์˜ 2์ œ๊ณฑ๋ช…์˜ ํ”ผ์•„๋…ธ ์กฐ์œจ์‚ฌ๊ฐ€ ์žˆ๋‹ค๊ณ  ๋งํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:31
we can say that there are approximately 10 to the second piano tuners in Chicago.
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03:34
Now, I know what you must be thinking:
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1832
์ž, ์ €๋Š” ์ง€๊ธˆ ์—ฌ๋Ÿฌ๋ถ„๋“ค์—๊ฒŒ ๋ฌด์Šจ ์ƒ๊ฐ์ด ๋“œ๋Š”์ง€ ์•Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค:
03:36
How can all of these estimates produce a reasonable answer?
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216820
2778
์–ด๋–ป๊ฒŒ ์ด ๋ชจ๋“  ์ถ”์ •๋“ค์ด ํƒ€๋‹นํ•œ ๋‹ต์„ ์ค„ ์ˆ˜ ์žˆ์„๊นŒ์š”?
03:39
Well, it's rather simple.
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์‚ฌ์‹ค ์ƒ๋‹นํžˆ ๊ฐ„๋‹จํ•ฉ๋‹ˆ๋‹ค: ํŽ˜๋ฅด๋ฏธ์˜ ๋ฌธ์ œ์—์„œ, ๊ณผ๋Œ€ ์ถ”์ •๊ณผ ๊ณผ์†Œ ์ถ”์ •์ด ์„œ๋กœ ๊ท ํ˜•์„ ์ด๋ฃฌ๋‹ค๊ณ  ๊ฐ€์ •ํ•ฉ๋‹ˆ๋‹ค,
03:41
In any Fermi problem, it is assumed
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03:42
that the overestimates and underestimates balance each other out,
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3127
๊ทธ๋ฆฌ๊ณ  ๋ณดํ†ต ์‹ค์ œ ํ•ด๋‹ต์—์„œ 1์ž๋ฆฌ์ˆ˜ ์ด๋‚ด ํฌ๊ธฐ๋กœ ์ถ”์ •์„ ํ•˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
03:46
and produce an estimation
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1215
03:47
that is usually within one order of magnitude of the actual answer.
80
227251
3240
ํ”ผ์•„๋…ธ ์กฐ์œจ์‚ฌ์˜ ์˜ˆ๋Š” ์‹œ์นด๊ณ ์˜ ์ „ํ™”๋ฒˆํ˜ธ๋ถ€์—์„œ ์กฐ์œจ์‚ฌ์˜ ์ˆซ์ž๋ฅผ ํ†ตํ•ด ํ™•์ธํ•ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:50
In our case we can confirm this by looking in the phone book
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03:53
for the number of piano tuners listed in Chicago.
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๋ช‡๋ช…์ผ๊นŒ์š”? 81๋ช…์ž…๋‹ˆ๋‹ค.
03:55
What do we find? 81.
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1634
03:57
Pretty incredible, given our order-of-magnitude estimation.
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์šฐ๋ฆฌ๊ฐ€ ํ•ด๋ณธ ํฌ๊ธฐ ์ถ”์ •์ด ์ƒ๋‹นํžˆ ์ •ํ™•ํ•˜์ฃ .
04:00
But, hey - that's the power of 10.
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ํ•˜์ง€๋งŒ, ๊ทธ๊ฒƒ์€ 10์˜ ์ œ๊ณฑ์ž…๋‹ˆ๋‹ค.
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

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