What is the kinetic energy distribution given the probability distribution?

In summary, the conversation discusses transforming a probability distribution for speed on a highway into a distribution for kinetic energy in order to analyze damages in crashes. The appropriate units for C and vo are hour/miles and the constant A is not necessary. The solution involves using the chain rule and making sure to substitute all occurrences of v with K. Dimensional analysis should be done to ensure correct units.
  • #1
jderm
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Homework Statement


Supose that a traffic study measures the speed at which people drive on the highway, and determines that the situation is well modeled by the probability distribution P(v)=Cv4e-v/vo. (a) If we are to measure speeds in mph, give the appropriate units for C and vo. (b) In order to perform an analysis of damages in crashes, transform that distribution into a distribution for kinetic energy.


Homework Equations


the product p(v)*dv is a dimensionless quantity.


The Attempt at a Solution


I understand that the units for dv are miles/hour, so p(v) is hour/miles.
therefore C must be in units (hour/miles)5

as for part B
K meaning kinetic energy
P(K)dK, dimensionless
i thinking that dK would be equal to .5*m*v*dv
and that P(K) would be P(v) multiplied by a constant 'A' (A having units hour/kg*mile)

so P(K)=ACv4e-v/vo units, (hour2/kg*mile2)
and dK=.5*m*v*dv units, (kg*mile2/hour2)

so if we were to intergrate,

fraction=p(k)*dk=p(k)*.5*m*v*dv=[tex]\frac{1}{2}[/tex]ACm[tex]\int[/tex]v5e-v/v0 dv

i think most people in the class just substituted 'v' with (2K/m)1/2, but i feel like that is incorrect, as you still need v to integrate.

is this the answer? is the constant 'A' necessary?
 
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  • #2
The probability distribution should really be

[tex]\frac{dP}{dv}=Cv^4e^{-v/v_0}[/tex]

To convert to kinetic energy, use the chain rule

[tex]\frac{dP}{dK}=\frac{dP}{dv}\frac{dv}{dK}[/tex]

You already have dP/dv but you need to calculate dv/dK.

Don't forget to change all occurrences of v into K, otherwise you will not have p(K). You do not need a separate constant A. When you are done, do dimensional analysis to make sure everything is in order.
 

FAQ: What is the kinetic energy distribution given the probability distribution?

What is a probability distribution?

A probability distribution is a mathematical function that describes the likelihood of different outcomes occurring in a random event. It assigns a probability to each possible outcome, with the total probability being equal to 1.

What are the types of probability distributions?

There are two main types of probability distributions: discrete and continuous. Discrete distributions are used for events with a finite number of outcomes, while continuous distributions are used for events with an infinite number of possible outcomes.

What is the difference between a probability distribution and a probability density function?

A probability distribution is a function that maps each possible outcome to a probability, while a probability density function is a function that describes the relative likelihood of different outcomes in a continuous distribution. In other words, a probability distribution gives the probability of a specific outcome, while a probability density function gives the probability of a range of outcomes.

How is a probability distribution represented graphically?

A probability distribution can be represented graphically in a variety of ways, depending on the type of distribution. For discrete distributions, a bar graph or histogram is commonly used, with the height of each bar representing the probability of a specific outcome. For continuous distributions, a line graph or curve is used to show the probability density function.

How is a probability distribution used in real life?

Probability distributions are used in many fields, including statistics, finance, and science. They are used to make predictions about the likelihood of certain outcomes, to analyze data, and to evaluate risk. For example, probability distributions are used in weather forecasting, stock market analysis, and medical research.

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