Why are so many phenomena exponentially distibuted?

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Discussion Overview

The discussion revolves around the prevalence of exponential distributions in various phenomena, exploring the underlying principles and potential explanations for their occurrence across different contexts, including productivity, wealth differences, and natural processes. Participants examine both exponential and power law distributions, questioning the fundamental reasons behind these patterns.

Discussion Character

  • Exploratory
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants note the frequent occurrence of exponential trends in daily life, citing examples from productivity, wealth, and natural phenomena.
  • One participant suggests that exponential distributions are solutions to the differential equation dy/dx = y, indicating a relationship where the rate of change depends on the current amount.
  • Another participant questions why the slope of exponential trends approaches zero as the dependent variable increases, suggesting a potential causal relationship.
  • Some participants propose that certain phenomena could also be modeled by power law distributions, raising questions about the prevalence of power laws and the conditions under which they apply.
  • It is mentioned that exponential distributions arise from random processes where events occur independently and continuously over time.
  • One participant discusses how real-world processes often depend on a relationship where the rate of change is proportional to the current amount, providing examples such as interest rates and production rates in factories.
  • A participant reflects on a specific phenomenon involving decision-making time increments and notes an exponential frequency distribution, questioning the reasons behind this observation.
  • Another participant references a paper discussing common patterns in nature, suggesting that different aggregation processes lead to different distribution patterns, including exponential and power law distributions.

Areas of Agreement / Disagreement

Participants express multiple competing views regarding the nature of exponential and power law distributions, and the discussion remains unresolved with respect to the fundamental principles governing these phenomena.

Contextual Notes

Participants highlight the complexity of modeling real-world phenomena, noting that assumptions about independence and continuity may influence the applicability of exponential distributions. The discussion also touches on the limitations of existing models in fully explaining observed distributions.

Helicobacter
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http://en.wikipedia.org/wiki/Exponential_family

I can't count the number of times I've encountered exponential trends in my daily life:
- Productivity
- Skill differences
- Wealth differences
Not even all socioeconomic: You can even find it in nature:
- the energy amplitude of an electron decreasing exponentially as you get away from the center
- your mass increasing as you approach the speed of light
or in business:
- the distribution of the length of phone calls to a call center...
- the salesvolume distribution of various products of a company
- the reasons of why certain products fail (Poisson charts)

There are many more examples (too many to count in other areas of the universe and life).

Why? What is the fundamental principle that is shared by all exponential trends?
 
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They're all solutions of the profoundly simple differential equation:

dy/dx = y

i.e. that the rate of change depends on the amount of change.
 
thats a good way of looking at it but there is a more profound explanation that I am missing. WHY does it drop less and less as the dependent variable gets bigger? why does the slope come closer and closer to 0. i read somewhere that it is due to some kind of causal relationship.
 
Helicobacter said:
I can't count the number of times I've encountered exponential trends in my daily life:
- Productivity
- Skill differences
- Wealth differences
[...]
- the distribution of the length of phone calls to a call center...
- the salesvolume distribution of various products of a company

Can't some of these be modeled by power law distributions as well?
 
thanks: that's what i actually meant.

however,my key questiosn are: why is the power law so prevalent? and why does any particular phenomenon obey that law?
 
Helicobacter said:
thats a good way of looking at it but there is a more profound explanation that I am missing. WHY does it drop less and less as the dependent variable gets bigger? why does the slope come closer and closer to 0. i read somewhere that it is due to some kind of causal relationship.
You get an exponential distribution for the time between events whenever the underlying events can happen at any point in time (i.e., continuous rather than discrete) and the events are independent from one another (i.e., the occurrence of an event neither excites nor inhibits the next occurrence).

There are lots of random processes that obey these two basic characteristics, and that is why you see so many exponential distributions.
 
oh so its mostly because you can have a set of arbitrary probabilities and then when they happen over and over again the result will be a skewed distribution ...even if the core probabilities are relatively close (.44^233 >> ..39^223)

thanks
 
Another reason these kinds of distributions show up a lot is that many real world processes depend on this "rate of change is proportional to the current amount" relationship. For example, the rate of change of your bank account depends entirely on some constant (your interest rate) times the amount in the bank account. If you have a 1% interest rate per year, $100 will grow by $1 but if you have $10,000 dollars, the amount will grow by $100. If a factory has twice as many workers, it will typically produce twice as many goods, if you have twice as much of a radioactive element, it will give off twice as much radiation, etc etc.
 
i was just thinking about another phenomenon which i can't explain...

when i give fritz 1sec, 10sec, 100sec, 1000sec time to think about a move, the times where the recommendation differs fewer times among the time increments is exponentially more common than all four differing say.

0 difference 70%
1 difference 20%
2 difference 9%
3 difference 1%

but what's weird is you already account for the EXPTIME of seeking a move by the time increments (increasing in decades)...so what explains the fact that a power family remains in the frequency distribution?
 
Last edited:
  • #10
Helicobacter said:
...my key questiosn are: why is the power law so prevalent? and why does any particular phenomenon obey that law?

This may be overkill for your purposes, but there is this excellent paper on the common patterns of nature - http://arxiv.org/abs/0906.3507

Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern.
 

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