A clever way to estimate enormous numbers - Michael Mitchell

1,033,004 views ใƒป 2012-09-12

TED-Ed


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืชืจื’ื•ื: Yifat Adler ืขืจื™ื›ื”: Nir Bibi
00:15
Whether you like it or not, we use numbers every day.
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ื‘ื™ืŸ ืฉืืชื ืื•ื”ื‘ื™ื ื–ืืช ื•ื‘ื™ืŸ ืฉืœื, ืื ื—ื ื• ืžืฉืชืžืฉื™ื ื‘ืžืกืคืจื™ื ื‘ื›ืœ ื™ื•ื.
00:18
Some numbers, such as the speed of sound,
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ื›ืžื” ืžืกืคืจื™ื, ื›ืžื• ืžื”ื™ืจื•ืช ื”ืงื•ืœ, ื”ื ืงื˜ื ื™ื ื•ืงืœ ืœืขื‘ื•ื“ ืื™ืชื.
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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ืžืกืคืจื™ื ืื—ืจื™ื, ื›ืžื• ืžื”ื™ืจื•ืช ื”ืื•ืจ, ื”ืจื‘ื” ื™ื•ืชืจ ื’ื“ื•ืœื™ื ื•ืžืกื•ืจื‘ืœื™ื ืœืขื‘ื•ื“ื”.
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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ื ื•ื›ืœ ืœื”ืฉืชืžืฉ ื‘ื›ืชื™ื‘ ืžื“ืขื™ ื›ื“ื™ ืœื‘ื˜ื ืžืกืคืจื™ื ื’ื“ื•ืœื™ื ื‘ื“ืจืš ื”ืจื‘ื” ื™ื•ืชืจ ื ื•ื—ื”.
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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ื•ื›ืš ื ื•ื›ืœ ืœื›ืชื•ื‘ 299,782,458 ืžื˜ืจื™ื ืœืฉื ื™ื™ื” ื›- 3.0 ื›ืคื•ืœ 10 ื‘ื—ื–ืงืช 8 ืžื˜ืจื™ื ืœืฉื ื™ื”.
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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ื‘ื›ืชื™ื‘ ืžื“ืขื™ ื ื›ื•ืŸ - ืขืจืš ื”ื‘ื™ื˜ื•ื™ ื”ืจืืฉื•ืŸ ื’ื“ื•ืœ ืž-1 ืืš ืงื˜ืŸ ืž-10,
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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ื•ื”ื‘ื™ื˜ื•ื™ ื”ืฉื ื™ ืžื™ื™ืฆื’ ืืช ื”ื—ื–ืงื” ืฉืœ 10, ืื• ืืช ืกื“ืจ ื”ื’ื•ื“ืœ ืฉื‘ื• ืžื›ืคื™ืœื™ื ืืช ื”ื’ื•ืจื ื”ืจืืฉื•ืŸ.
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 ืœื”ืฉืชืžืฉ ื‘ื—ื–ืงื” ืฉืœ 10 ื›ื›ืœื™ ืœื‘ื™ืฆื•ืข ื”ืขืจื›ื•ืช ืžื”ื™ืจื•ืช ื›ืฉืื™ื ื ื• ื–ืงื•ืงื™ื ืœืขืจื›ื• ื”ืžื“ื•ื™ื™ืง ืฉืœ ืžืกืคืจ.
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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ืœื“ื•ื’ืžื, ืงื•ื˜ืจื• ืฉืœ ืื˜ื•ื ื”ื•ื ื‘ืงื™ืจื•ื‘ 10 ื‘ื—ื–ืงืช 12- ืžื˜ืจื™ื.
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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ื’ื•ื‘ื”ื• ืฉืœ ืขืฅ ื”ื•ื ื‘ืงื™ืจื•ื‘ 10 ื‘ื—ื–ืงืช 1 ืžื˜ืจื™ื.
01:07
The diameter of the Earth is approximately 10 to the power of seven meters.
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ื•ืงื•ื˜ืจื• ืฉืœ ื›ื“ื•ืจ ื”ืืจืฅ ื”ื•ื ื‘ืงื™ืจื•ื‘ 10 ื‘ื—ื–ืงืช 7 ืžื˜ืจื™ื.
ื”ื™ื›ื•ืœืช ืœื”ืฉืชืžืฉ ื‘ื—ื–ืงื•ืช ืฉืœ 10 ื›ื›ืœื™ ืœื”ืขืจื›ื” ื™ื›ื•ืœื” ืœื”ื™ื•ืช ืฉื™ืžื•ืฉื™ืช ื‘ื”ื–ื“ืžื ื•ื™ื•ืช ืฉื•ื ื•ืช,
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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ื›ืžื• ืœืžืฉืœ ื›ืฉืืชื ืžื ืกื™ื ืœื ื—ืฉ ื›ืžื” ืกื•ื›ืจื™ื•ืช M&M ื™ืฉ ื‘ืฆื ืฆื ืช.
ื–ื•ื”ื™ ื’ื ืžื™ื•ืžื ื•ืช ื—ืฉื•ื‘ื” ื‘ืžืชืžื˜ื™ืงื” ื•ื‘ืžื“ืขื™ื, ื‘ืžื™ื•ื—ื“ ื›ืฉืขื•ืกืงื™ื ื‘ื‘ืขื™ื•ืช ื”ืžื•ื›ืจื•ืช ื›ื‘ืขื™ื•ืช ืคืจืžื™.
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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ื‘ืขื™ื•ืช ืคืจืžื™ ืงืจื•ื™ื•ืช ืขืœ ืฉืžื• ืฉืœ ื”ืคื™ื–ื™ืงืื™ ืื ืจื™ืงื• ืคืจืžื™, ื”ืžืคื•ืจืกื ื‘ื‘ื™ืฆื•ืข ื”ืขืจื›ื•ืช ืžื”ื™ืจื•ืช ืฉืœ ืกื“ืจ ื’ื•ื“ืœ,
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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ืื• ื”ืขืจื›ื•ืช ืžื”ื™ืจื•ืช ื”ืžืกืชืžื›ื•ืช ืขืœ ืžื™ื“ืข ืžื•ื’ื‘ืœ ืœื›ืื•ืจื”.
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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ืคืจืžื™ ืขื‘ื“ ื‘ืคืจื•ื™ืงื˜ ืžื ื”ื˜ืŸ ื‘ืคื™ืชื•ื— ื”ืคืฆืฆื” ื”ืื˜ื•ืžื™ืช,
01:35
and when it was tested at the Trinity site in 1945,
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ื•ื›ืืฉืจ ื‘ื•ืฆืข ื ื™ืกื•ื™ ื‘ืืชืจ ื˜ืจื™ื ื™ื˜ื™ ื‘ืฉื ืช 1945, ืคืจืžื™ ื”ืฉืœื™ืš ืžืกืคืจ ืคื™ืกื•ืช ื ื™ื™ืจ ื‘ื–ืžืŸ ื”ืคื™ืฆื•ืฅ
01:38
Fermi dropped a few pieces of paper during the blast
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ื•ื”ืฉืชืžืฉ ื‘ืžืจื—ืง ืฉื‘ื• ื”ืŸ ืขืคื• ืื—ื•ืจื ื™ืช ื‘ืฉืขื” ืฉื ืคืœื• ื›ื“ื™ ืœื”ืขืจื™ืš ืืช ืขื•ืฆืžืช ื”ืคื™ืฆื•ืฅ
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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ื›-10 ืงื™ืœื•ื˜ื•ืŸ ืฉืœ ื˜ื™.ืืŸ.ื˜ื™., ืฉื”ื•ื ื‘ืื•ืชื• ืกื“ืจ ื’ื•ื“ืœ ืฉืœ ื”ืขืจืš ื”ืืžื™ืชื™ 20 ืงื™ืœื•ื˜ื•ืŸ.
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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ื“ื•ื’ืžื ืœื‘ืขื™ื•ืช ื”ืขืจื›ืช ืคืจืžื™ ืงืœืืกื™ื•ืช ื”ื™ื: ื›ืžื” ืžื›ื•ื•ื ื™ ืคืกื ืชืจื™ื ื™ืฉื ื ื‘ืฉื™ืงื’ื•, ืื™ืœื™ื ื•ื™?
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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ื‘ืชื—ื™ืœื” ื ื“ืžื” ืฉื™ืฉ ื™ื•ืชืจ ืžื“ื™ ื“ื‘ืจื™ื ืœื ื™ื“ื•ืขื™ื ื•ืฉื”ื‘ืขื™ื” ื‘ืœืชื™ ืคืชื™ืจื”.
02:01
that the problem appears to be unsolvable.
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ื–ื•ื”ื™ ื“ื•ื’ืžื ืžื•ืฉืœืžืช ืœื™ื™ืฉื•ื ื”ืขืจื›ื” ื‘ืืžืฆืขื•ืช ื—ื–ืงื•ืช ืฉืœ 10, ืžื›ื™ื•ื•ืŸ ืฉืื™ื ื ื• ื–ืงื•ืงื™ื ืœืชืฉื•ื‘ื” ืžื“ื•ื™ื™ืงืช.
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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ื”ืขืจื›ื” ืžืกืคืงืช ืื•ืชื ื•.
02:09
We can start by determining how many people live in the city of Chicago.
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ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื”ืชื—ื™ืœ ื‘ืงื‘ื™ืขื” ื›ืžื” ืื ืฉื™ื ื’ืจื™ื ื‘ืฉื™ืงื’ื•.
02:12
We know that it is a large city,
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ืื ื—ื ื• ื™ื•ื“ืขื™ื ืฉื–ื•ื”ื™ ืขื™ืจ ื’ื“ื•ืœื”. ืื•ืœื™ ืื™ื ื ื• ื‘ื˜ื•ื—ื™ื ื›ืžื” ืื ืฉื™ื ื‘ื“ื™ื•ืง ื’ืจื™ื ื‘ืขื™ืจ.
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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ืžื™ืœื™ื•ืŸ ืื ืฉื™ื? ื—ืžื™ืฉื” ืžื™ืœื™ื•ืŸ?
02:20
This is the point in the problem
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ื‘ื ืงื•ื“ื” ื”ื–ื•, ืื ืฉื™ื ืจื‘ื™ื ื ืขืฉื™ื ืžืชื•ืกื›ืœื™ื ืข"ื™ ื—ื•ืกืจ ื”ื•ื•ื“ืื•ืช.
02:22
where many people become frustrated with the uncertainty,
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ืื‘ืœ ืื ื—ื ื• ื™ื›ื•ืœื™ื ื‘ืงืœื•ืช ืœื”ืชื’ื‘ืจ ืขืœ ื›ืš ื‘ืืžืฆืขื•ืช ื—ื–ืงื•ืช ืฉืœ 10.
02:25
but we can easily get through this by using the power of 10.
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ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื”ืขืจื™ืš ืืช ืกื“ืจ ื”ื’ื•ื“ืœ ืฉืœ ืื•ื›ืœื•ืกื™ืช ืฉื™ืงื’ื• ื›-10 ื‘ื—ื–ืงืช 6.
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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ื”ื‘ื™ื˜ื•ื™ ืœื ืžืฆื™ื™ืŸ ื›ืžื” ืื ืฉื™ื ื’ืจื™ื ืฉื ื‘ื“ื™ื•ืง,
02:35
it serves an accurate estimation for the actual population
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ืืš ื”ื•ื ื”ืขืจื›ื” ืžื“ื•ื™ืงืช ืฉืœ ื’ื•ื“ืœ ื”ืื•ื›ืœื•ืกื™ื” ืฉื”ื™ื ื• ืงืฆืช ืคื—ื•ืช ืž-3 ืžืœื™ื•ืŸ ืื ืฉื™ื.
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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ื•ื›ืš, ืื ื™ืฉื ื ื›-10 ื‘ื—ื–ืงืช 6 ืื ืฉื™ื ื‘ืฉื™ืงื’ื•, ื›ืžื” ืคืกื ืชืจื™ื ื™ืฉ ืฉื?
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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ืื ื ืจืฆื” ืœื”ืžืฉื™ืš ืœื”ืฉืชืžืฉ ื‘ืกื“ืจื™ ื’ื•ื“ืœ ื ื•ื›ืœ ืœื•ืžืจ
02:47
we can either say that one out of 10
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ืฉืœ-1 ืžืชื•ืš 10 ืื• ืœ-1 ืžืชื•ืš 100 ืื ืฉื™ื ื™ืฉ ืคืกื ืชืจ.
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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ืžื›ื™ื•ื•ืŸ ืฉื”ื”ืขืจื›ื” ืฉืœ ื”ืื•ื›ืœื•ืกื™ื” ื›ื•ืœืœืช ื™ืœื“ื™ื ื•ืžื‘ื•ื’ืจื™ื, ื ืฉืชืžืฉ ื‘ื”ืขืจื›ื” ื”ืฉื ื™ื”
02:55
we'll go with the latter estimate,
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ืฉืžืขืจื™ื›ื” ืฉื™ืฉ ื›-10 ื‘ื—ื–ืงืช 4 ืื• 10,000 ืคืกื ืชืจื™ื ื‘ืฉื™ืงื’ื•.
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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ืื ื–ื•ื”ื™ ื›ืžื•ืช ื”ืคืกื ืชืจื™ื, ื›ืžื” ืžื›ื•ื•ื ื™ ืคืกื ืชืจื™ื ื™ืฉ ื‘ืฉื™ืงื’ื•?
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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ื”ื™ื™ื ื• ื™ื›ื•ืœื™ื ืœื”ืชื—ื™ืœ ืืช ืชื”ืœื™ืš ื”ื—ืฉื™ื‘ื” ื‘ืฉืืœื” ื‘ืื™ื–ื• ืชื“ื™ืจื•ืช ืžื›ื•ื•ื ื™ื ืคืกื ืชืจื™ื,
ื›ืžื” ืคืกื ืชืจื™ื ืžื›ื•ื•ื ื™ื ื‘ื›ืœ ื™ื•ื, ืื• ื›ืžื” ื™ืžื™ ืขื‘ื•ื“ื” ื™ืฉ ืœืžื›ื•ื•ืŸ ืคืกื ืชืจื™ื,
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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ืืš ืœื ื–ื•ื”ื™ ื”ื ืงื•ื“ื” ื‘ื”ืขืจื›ื” ืžื”ื™ืจื”.
03:15
We instead think in orders of magnitude,
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ื‘ืžืงื•ื ื–ืืช, ื ื—ืฉื•ื‘ ื‘ืกื“ืจื™ ื’ื•ื“ืœ ื•ื ืืžืจ ืฉืžื›ื•ื•ืŸ ืคืกื ืชืจื™ื ืžื›ื•ื•ืŸ ื›-10 ื‘ื—ื–ืงืช 2 ืคืกื ืชืจื™ื ื‘ืฉื ื”.
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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ืฉื”ื ื‘ืขืจืš ื›ืžื” ืžืื•ืช ืคืกื ืชืจื™ื.
03:23
Given our previous estimate of 10 to the fourth pianos in Chicago,
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ื‘ื”ื ืชืŸ ื”ื”ืขืจื›ื” ื”ืงื•ื“ืžืช ืฉืœื ื• ืฉืœ 10 ื‘ื—ื–ืงืช 4 ืคืกื ืชืจื™ื ื‘ืฉื™ืงื’ื•,
03:26
and the estimate that each piano tuner can tune 10 to the second pianos each year,
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ื•ื”ื”ืขืจื›ื” ืฉื›ืœ ืžื›ื•ื•ืŸ ืคืกื ืชืจื™ื ื™ื›ื•ืœ ืœื›ื•ื•ืŸ 10 ื‘ื—ื–ืงืช 2 ืคืกื ืชืจื™ื ื‘ืฉื ื”,
ื ื•ื›ืœ ืœื•ืžืจ ืฉื™ืฉ ื‘ืขืจืš 10 ื‘ื—ื–ืงืช 2 ืžื›ื•ื•ื ื™ ืคืกื ืชืจื™ื ื‘ืฉื™ืงื’ื•.
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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ืื ื™ ื™ื•ื“ืข ืžื” ืืชื ื—ื•ืฉื‘ื™ื ื›ืขืช:
03:36
How can all of these estimates produce a reasonable answer?
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ืื™ืš ื›ืœ ื”ื”ืขืจื›ื•ืช ื”ืืœื” ื™ื›ื•ืœื•ืช ืœื”ื‘ื™ื ืœืชืฉื•ื‘ื” ื”ื’ื™ื•ื ื™ืช?
03:39
Well, it's rather simple.
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ื•ื‘ื›ืŸ, ื–ื” ืคืฉื•ื˜ ืœืžื“ื™: ื‘ื›ืœ ื‘ืขื™ืช ืคืจืžื™ ืžื ื™ื—ื™ื ืฉื”ืขืจื›ื•ืช ื™ืชืจ ืžืชืงื–ื–ื•ืช ืขื ื”ืขืจื›ื•ืช ื—ืกืจ
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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ื•ื™ื•ืฆืจื•ืช ื”ืขืจื›ื” ืฉื”ื™ื ื‘ื“ืจืš ื›ืœืœ ื‘ื˜ื•ื•ื— ืฉืœ ืกื“ืจ ื’ื•ื“ืœ ืื—ื“ ืžื”ืชืฉื•ื‘ื” ื”ืืžื™ืชื™ืช.
03:46
and produce an estimation
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03:47
that is usually within one order of magnitude of the actual answer.
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ื‘ืžืงืจื” ืฉืœื ื•, ื ื•ื›ืœ ืœืืฉืจ ื–ืืช ืื ื ื‘ื“ื•ืง ื‘ืกืคืจ ื”ื˜ืœืคื•ื ื™ื ื›ืžื” ืžื›ื•ื•ื ื™ ืคืกื ืชืจื™ื ืจืฉื•ืžื™ื ื‘ืฉื™ืงื’ื•.
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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ื•ืžื” ื ืžืฆื ืฉื? 81.
03:55
What do we find? 81.
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03:57
Pretty incredible, given our order-of-magnitude estimation.
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ื“ื™ ืžื“ื”ื™ื, ื”ื ืชื—ืฉื‘ ื‘ื”ืขืจื›ื” ื‘ื”ืขืจื›ื” ืฉืœ ืกื“ืจ ื”ื’ื•ื“ืœ ืฉืœื ื•.
04:00
But, hey - that's the power of 10.
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ืื‘ืœ, ื”ื™, ื–ื”ื• ื—ื•ื–ืงื• ืฉืœ ื”ืขืฉืจ.
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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