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Benford's law explanation (sequel to mysteries of Benford's law) Video Lecture - Engineering Mathematics
FAQs on Benford's law explanation (sequel to mysteries of Benford's law) Video Lecture - Engineering Mathematics
| 1. What is Benford's law and how does it relate to engineering mathematics? |  |
Benford's law, also known as the first-digit law, states that in many sets of numerical data, the leading digit is more likely to be small (1, 2, 3) rather than large (8, 9). It has been observed to hold for various real-life data, including engineering measurements and mathematical models. The law is relevant in engineering mathematics as it helps in analyzing and detecting anomalies in data sets, such as identifying fraud or errors in financial statements or quality control processes.
| 2. Can you provide an intuitive explanation of why Benford's law holds true? | |
Benford's law can be intuitively explained by considering the relative distribution of numbers in a real-life context. For example, when we look at populations, the number of people with ages starting with a small digit (1, 2, 3) is usually much larger than those starting with a larger digit (8, 9). Similarly, in financial transactions, smaller amounts occur more frequently than larger amounts. Benford's law captures this underlying pattern and provides a mathematical explanation for the observed distribution of leading digits.
| 3. What are some practical applications of Benford's law in engineering mathematics? | |
Benford's law finds practical applications in various fields of engineering mathematics. Some examples include:
- Fraud detection: Benford's law can be used to identify anomalies in financial statements, tax returns, or any data involving numerical values. If a dataset deviates significantly from the expected distribution, it may indicate potential fraud or errors.
- Quality control: Benford's law can be applied to quality control processes, such as monitoring the conformity of measurements or detecting outliers in manufacturing processes.
- Data validation: It can be used as a tool to validate the accuracy and reliability of data collected in engineering experiments or simulations.
- Forensic analysis: Benford's law has been utilized in forensic analysis to detect manipulations or forgeries in digital images, audio recordings, or other forms of digital data.
| 4. Are there any limitations or exceptions to Benford's law? | |
While Benford's law is a useful tool, it is important to note its limitations and exceptions. Some factors that can affect the applicability of Benford's law include:
- Small sample sizes: Benford's law is more reliable with larger datasets. Smaller datasets may not exhibit the expected distribution.
- Contextual variations: Different types of data may have different distributions, and Benford's law may not hold true in all cases. For example, certain datasets with specific constraints or characteristics may deviate from the expected distribution.
- Deliberate manipulation: In some cases, data may be intentionally manipulated to conform to or deviate from Benford's law. This can be done to deceive or mislead data analysis.
- Cultural or regional variations: Benford's law is based on observations from various datasets worldwide. However, cultural or regional variations may influence the distribution of leading digits, leading to deviations from the expected pattern.
| 5. How can engineers effectively apply Benford's law in their data analysis processes? | |
To effectively apply Benford's law in data analysis, engineers can follow these steps:
1. Understand the context: Consider the nature and characteristics of the dataset being analyzed. Assess whether Benford's law is expected to hold or if there are factors that may affect its applicability.
2. Collect sufficient data: Ensure that the dataset is large enough to generate meaningful results. Larger datasets provide more reliable outcomes.
3. Conduct statistical analysis: Compare the distribution of leading digits in the dataset against the expected distribution based on Benford's law. Use statistical tests to assess the level of conformity or deviation.
4. Interpret results: Analyze the findings and identify any significant deviations from the expected distribution. Investigate the possible causes of such deviations, such as errors, fraud, or other anomalies.
5. Take appropriate actions: Based on the analysis, take appropriate actions such as data validation, further investigation, or implementing corrective measures to address any identified issues.
By following these steps, engineers can leverage Benford's law as a valuable tool in their data analysis processes, enabling them to detect irregularities and make informed decisions based on reliable data.
Text Transcript from Video
SAL: So where we left
off in the last video,
Vi and myself had
posed a mystery to you.
We had talked about
Benford's law.
VI: And we asked, what
is up with Benford's law?
SAL: This idea that, if you
took just random countries
and took their population and
took the most significant digit
in their population and plotted
the numbers of countries
that their most significant
digit is a 1, versus a 2,
versus a 3, you just
had it was much more
likely that it would be a 1.
Or that, if you took physical
constants of the universe,
that they're most
likely to have 1
as their most significant digit.
VI: I wish we had more graphs,
because graphs are fun.
SAL: Yes.
VI: But if you
look at information
from the stock market
or anything, what's up?
SAL: Yes.
And it seems to all
follow this curve.
And what was
extremely mysterious--
and this is where we
finished off the last video--
was if you look at
pure, I would say,
compounding phenomenon, like
for example, the Fibonacci
sequence, or powers of 2,
that exactly fits the Benford
distribution.
It exactly fits this.
If you take all the
powers of 2, a little bit
over 30% of those powers of
2, all of the powers of 2
have 1 as their most
significant digit.
What is this?
17?
Roughly 17% of
all of them have 2
as their most significant digit.
VI: Yeah.
Although in this case,
there's an infinite number
in every set, so
it's harder to graph.
SAL: But if you
wanted to try it out,
you could take the first
million powers of 2
and then find the percentage.
And that will probably give
you a pretty good approximation
of things.
VI: Yeah.
So to me, that's
like less mysterious.
On the one hand, wow, this
fits exactly with mathematics.
But that also gives you
a really good handle,
because you realize, alright,
there's something here
I can actually take a look at.
SAL: You could take
a look at it and it
starts to become something
you can dig deeper in.
And we said, in
the last video, we
wanted you to pause it and think
about why this is happening
because, frankly, we had
to do the same thing.
And a big clue
for us was when we
looked at a logarithmic scale.
And we're looking at
one right over here.
And just to be clear,
what's going on
in this logarithmic scale is you
see equal spaces on this scale
are powers of 10.
So on a linear scale,
this would be a 1.
And maybe this would
be a 2 and then a 3.
Or if we wanted to
say that this is a 2,
you would say this is a 1, this
is a 10, this would be a 20,
then would be a 30,
so on and so forth.
But in a logarithmic
scale, equal distances
are times 10 or, in this case,
if we're taking powers of 10.
So this is 1:10, then
10:100, then 100:1,000.
And you see how the numbers
in between fall out,
that the space between
1 and 2 is pretty big.
And then 2 and 3 is still pretty
big, but a little bit smaller.
And then 3 and 4 gets smaller
and smaller and smaller,
until you get to 10.
And that's a pretty
big clue about what's
going on with Benford's law.
VI: Yeah.
It seems to match up somehow.
So there's a connection here.
SAL: And it actually turns out--
and this actually a very big
clue-- that this, if
you take this area right
here as a percentage
of this entire area,
it's exactly this percentage.
It's exactly that
percentage there.
And if you take this area as a
percentage of that entire area,
it's exactly this
percentage, that roughly 17%,
or whatever that number
is right over there.
So that's a huge clue.
VI: Yeah, or at
least for powers of 2
or a Fibonacci sequence
thing-- for powers,
it definitely makes sense.
SAL: Yes, for any powers.
And so the logic
is-- and this is now
our biggest clue-- is to
actually plot the powers of 2
on a logarithmic
scale like this.
VI: All right, let's
see where they fall.
SAL: All right,
let's try it out.
So 2 to the zeroth power is 1.
2 to the first power is 2.
Then you get to 4.
Then you get to 8.
Then you get to
16, which is going
to be someplace around here.
Then you want to
go to 32, which is
going to be someplace
around there.
That's 30, so this is 32.
Then you want to go to 64.
And so this is 40, 50, 60.
64 is going to be
right over there.
And so what you see is, when
you plot the powers of 2
on this logarithmic scale,
they're equal distance apart.
So you keep stepping along.
If you were to plot
on a linear scale,
they'd get farther
and farther apart.
VI: Yeah.
SAL: Actually, twice as
far apart every time.
But on this scale right over
here they are equally spaced.
So what's happening
is you have something
that's just equally
stepping along here.
You can imagine even just
like walking along this.
And if your sidewalk is shaped
like this logarithmic scale,
the probability on
any given step, as you
do many, many steps, or as
you count all the steps,
you're going to have
many, many more steps that
fall into the block
that's between 1 and 2,
or between 10 and
20, than you will,
for example, the block
that's between 9 and 10.
VI: Yeah, if you just take
a random point along here,
you're more likely to fall
in a area starting with 1.
SAL: Right, one of these areas.
Exactly, starting with 1, so
between 1 and 2, or 10 and 20,
or 100 and-- and
that's exactly--
VI: So taking equal steps
is going to give you
that distribution, unless
your steps happen to--
because there's
special cases, right?
So if you're getting--
SAL: Or people walk
logarithmically.
[LAUGHS]
VI: Yeah, if you walk from 1 to
10, if your steps are 10 long--
SAL: Yeah.
In special cases, yes.
VI: So that's what
happens there.
SAL: If your steps are 10 long--
VI: You happen to
exactly on [INAUDIBLE].
SAL: Right.
But if you're anything--
any slight variation
away from that exact
thing, and then you
will get the distribution.
VI: Yeah.
You're going to end up
stepping all over the place.
SAL: The Benford's distribution.
VI: Benford's distribution.
SAL: Even though I think
we now understand why,
it's still fascinating.
VI: Yeah.
Well, this explains it
for these number series.
SAL: Yes.
VI: So now we have
to somehow figure out
how to connect that to the
real world information.
SAL: The general idea,
well, so for populations.
And we read up a
little about it.
And Benford's
distribution tends to work
for things that
grow exponentially.
VI: Yes.
SAL: Like powers of 2.
VI: Like powers of 2.
SAL: Like powers of 2.
And populations
grow exponentially.
VI: Yeah.
And in finance, a lot of
things also grow exponentially.
SAL: Yes.
Or decline exponentially.
Either way.
[LAUGHTER]
SAL: But it tends to
operate exponentially.
You keep growing
by 10% every year.
That's an exponential path.
What's fascinating is
physical constants.
And we actually aren't 100%
sure why this is happening.
VI: No.
This is still crazy to me.
SAL: We only have theories here.
And the general idea--
because, you know,
physical constants is sort
of dependent on the units
you're dealing with.
They're depending on a
whole bunch of things.
Actually, I have a few
very loose theories.
But I'll let you all
think about that more.
VI: OK.
SAL: All right?
And so, hopefully,
you all enjoyed this.
off in the last video,
Vi and myself had
posed a mystery to you.
We had talked about
Benford's law.
VI: And we asked, what
is up with Benford's law?
SAL: This idea that, if you
took just random countries
and took their population and
took the most significant digit
in their population and plotted
the numbers of countries
that their most significant
digit is a 1, versus a 2,
versus a 3, you just
had it was much more
likely that it would be a 1.
Or that, if you took physical
constants of the universe,
that they're most
likely to have 1
as their most significant digit.
VI: I wish we had more graphs,
because graphs are fun.
SAL: Yes.
VI: But if you
look at information
from the stock market
or anything, what's up?
SAL: Yes.
And it seems to all
follow this curve.
And what was
extremely mysterious--
and this is where we
finished off the last video--
was if you look at
pure, I would say,
compounding phenomenon, like
for example, the Fibonacci
sequence, or powers of 2,
that exactly fits the Benford
distribution.
It exactly fits this.
If you take all the
powers of 2, a little bit
over 30% of those powers of
2, all of the powers of 2
have 1 as their most
significant digit.
What is this?
17?
Roughly 17% of
all of them have 2
as their most significant digit.
VI: Yeah.
Although in this case,
there's an infinite number
in every set, so
it's harder to graph.
SAL: But if you
wanted to try it out,
you could take the first
million powers of 2
and then find the percentage.
And that will probably give
you a pretty good approximation
of things.
VI: Yeah.
So to me, that's
like less mysterious.
On the one hand, wow, this
fits exactly with mathematics.
But that also gives you
a really good handle,
because you realize, alright,
there's something here
I can actually take a look at.
SAL: You could take
a look at it and it
starts to become something
you can dig deeper in.
And we said, in
the last video, we
wanted you to pause it and think
about why this is happening
because, frankly, we had
to do the same thing.
And a big clue
for us was when we
looked at a logarithmic scale.
And we're looking at
one right over here.
And just to be clear,
what's going on
in this logarithmic scale is you
see equal spaces on this scale
are powers of 10.
So on a linear scale,
this would be a 1.
And maybe this would
be a 2 and then a 3.
Or if we wanted to
say that this is a 2,
you would say this is a 1, this
is a 10, this would be a 20,
then would be a 30,
so on and so forth.
But in a logarithmic
scale, equal distances
are times 10 or, in this case,
if we're taking powers of 10.
So this is 1:10, then
10:100, then 100:1,000.
And you see how the numbers
in between fall out,
that the space between
1 and 2 is pretty big.
And then 2 and 3 is still pretty
big, but a little bit smaller.
And then 3 and 4 gets smaller
and smaller and smaller,
until you get to 10.
And that's a pretty
big clue about what's
going on with Benford's law.
VI: Yeah.
It seems to match up somehow.
So there's a connection here.
SAL: And it actually turns out--
and this actually a very big
clue-- that this, if
you take this area right
here as a percentage
of this entire area,
it's exactly this percentage.
It's exactly that
percentage there.
And if you take this area as a
percentage of that entire area,
it's exactly this
percentage, that roughly 17%,
or whatever that number
is right over there.
So that's a huge clue.
VI: Yeah, or at
least for powers of 2
or a Fibonacci sequence
thing-- for powers,
it definitely makes sense.
SAL: Yes, for any powers.
And so the logic
is-- and this is now
our biggest clue-- is to
actually plot the powers of 2
on a logarithmic
scale like this.
VI: All right, let's
see where they fall.
SAL: All right,
let's try it out.
So 2 to the zeroth power is 1.
2 to the first power is 2.
Then you get to 4.
Then you get to 8.
Then you get to
16, which is going
to be someplace around here.
Then you want to
go to 32, which is
going to be someplace
around there.
That's 30, so this is 32.
Then you want to go to 64.
And so this is 40, 50, 60.
64 is going to be
right over there.
And so what you see is, when
you plot the powers of 2
on this logarithmic scale,
they're equal distance apart.
So you keep stepping along.
If you were to plot
on a linear scale,
they'd get farther
and farther apart.
VI: Yeah.
SAL: Actually, twice as
far apart every time.
But on this scale right over
here they are equally spaced.
So what's happening
is you have something
that's just equally
stepping along here.
You can imagine even just
like walking along this.
And if your sidewalk is shaped
like this logarithmic scale,
the probability on
any given step, as you
do many, many steps, or as
you count all the steps,
you're going to have
many, many more steps that
fall into the block
that's between 1 and 2,
or between 10 and
20, than you will,
for example, the block
that's between 9 and 10.
VI: Yeah, if you just take
a random point along here,
you're more likely to fall
in a area starting with 1.
SAL: Right, one of these areas.
Exactly, starting with 1, so
between 1 and 2, or 10 and 20,
or 100 and-- and
that's exactly--
VI: So taking equal steps
is going to give you
that distribution, unless
your steps happen to--
because there's
special cases, right?
So if you're getting--
SAL: Or people walk
logarithmically.
[LAUGHS]
VI: Yeah, if you walk from 1 to
10, if your steps are 10 long--
SAL: Yeah.
In special cases, yes.
VI: So that's what
happens there.
SAL: If your steps are 10 long--
VI: You happen to
exactly on [INAUDIBLE].
SAL: Right.
But if you're anything--
any slight variation
away from that exact
thing, and then you
will get the distribution.
VI: Yeah.
You're going to end up
stepping all over the place.
SAL: The Benford's distribution.
VI: Benford's distribution.
SAL: Even though I think
we now understand why,
it's still fascinating.
VI: Yeah.
Well, this explains it
for these number series.
SAL: Yes.
VI: So now we have
to somehow figure out
how to connect that to the
real world information.
SAL: The general idea,
well, so for populations.
And we read up a
little about it.
And Benford's
distribution tends to work
for things that
grow exponentially.
VI: Yes.
SAL: Like powers of 2.
VI: Like powers of 2.
SAL: Like powers of 2.
And populations
grow exponentially.
VI: Yeah.
And in finance, a lot of
things also grow exponentially.
SAL: Yes.
Or decline exponentially.
Either way.
[LAUGHTER]
SAL: But it tends to
operate exponentially.
You keep growing
by 10% every year.
That's an exponential path.
What's fascinating is
physical constants.
And we actually aren't 100%
sure why this is happening.
VI: No.
This is still crazy to me.
SAL: We only have theories here.
And the general idea--
because, you know,
physical constants is sort
of dependent on the units
you're dealing with.
They're depending on a
whole bunch of things.
Actually, I have a few
very loose theories.
But I'll let you all
think about that more.
VI: OK.
SAL: All right?
And so, hopefully,
you all enjoyed this.
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Oct 22, 2025
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