Probability Distribution and Constants

In summary: No, you won't be integrating anything because the energies are discrete - not continuous. Basically what you will do is to multiply the energy of each state by its probability and sum over all four states. This will give you the average energy for the given temperature provided you normalized properly per our eariler discussion.
  • #1
Rachael_Victoria
16
0
Hi,
I just started a physical chemistry class and we are working on probability theory. The questions I am having a hard time with are as follow:
we are given that E is proportional to exp[-E/RT]. It is stated that this is a simple system having only four energy states numbered 1 through 4.
The values for each energy state are E1=0 J/mol, E2= 1000 J/mol, E3= 2000 J/mol, and E4= 3000 J/mol.
The first question asks us to obtain the normalized probability distribution for the system in state i, and evaluate the normalization constant C at T=298K.
So I did it like this P(Ei) = C exp [-Ei/RT], and C= the sum of [(-E1/RT)-(E2/RT)-(E3/RT)-(E4/RT)]^-1
this once you crunch the numbers equals 1/2.4119835807817
So P(Ei)= (exp [-E/RT])/2.4119835807817
So my first question is did I do this correctly? The normalized probability distribution for the system in state i would simply be the formula above correct?
The second question asks us to calculate the average energy per system that a large number of such systems would have at 298K.
My question is should I do an integral from 0 to infinity?
so <P(E)>= (integral [E exp(-E/RT)])/(integral [-E/RT]) from 0 to infinity?
This might all be completely wrong. I don't have the solution manual and therefore cannot check my answers. If it is wrong if someone could explain how it is wrong I would really appreciate it.
Thanks,
Rachael
 
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  • #2
The probabilities should add up to 1, i.e. it is a certainty that the system will be in one of those states. That means multiplying by the reciprocal of the number you found rather than multiplying.
 
  • #3
Tide said:
The probabilities should add up to 1, i.e. it is a certainty that the system will be in one of those states. That means multiplying by the reciprocal of the number you found rather than multiplying.
I see what you are saying, they way our book presents it is that C is equal to 1 over the equation. So we got the entire C=1/[P(Xi)] thing. Here is the exact question as it is worded in my book: "...we shall find that the probability of a system occupying an energy state with energy E is proportional to exp[-E/RT]. Consider a simple system with having only four possible energy states..."

A) Obtain the normalized probability distribution for the system in state i.

I got P(Ei) = C exp [-Ei/RT]

and for C I got 1/( C= the sum of [(-E1/RT)-(E2/RT)-(E3/RT)-(E4/RT)])

B) Calculate the average energy per sysem that a large number of such systems would have at 298K.

My question here is am I calculating C using the integral of exp [-E/RT] from 0 to infinity and then using that C to find P(Xi)?
THanks
Rachael
 
  • #4
No, you won't be integrating anything because the energies are discrete - not continuous. Basically what you will do is to multiply the energy of each state by its probability and sum over all four states. This will give you the average energy for the given temperature provided you normalized properly per our eariler discussion.
 

What is a probability distribution?

A probability distribution is a mathematical function that describes the likelihood of different outcomes occurring in an experiment or event. It assigns probabilities to each possible outcome, with the sum of all probabilities equaling 1.

What are the types of probability distributions?

There are several types of probability distributions, including the normal distribution, binomial distribution, Poisson distribution, and exponential distribution. These distributions are characterized by their own unique shapes and properties.

What is a constant in a probability distribution?

A constant in a probability distribution is a fixed value that does not change. In some distributions, such as the normal distribution, the mean and standard deviation are constants that determine the shape and location of the distribution.

How is a probability distribution graphically represented?

A probability distribution can be represented graphically using a histogram or a curve on a graph. The x-axis represents the possible outcomes and the y-axis represents the probabilities. The shape of the graph can provide information about the distribution, such as whether it is symmetric or skewed.

How do you calculate probabilities using a probability distribution?

To calculate probabilities using a probability distribution, you can use the cumulative distribution function (CDF) or the probability density function (PDF). The CDF gives the probability that a random variable will take on a value less than or equal to a given value, while the PDF gives the probability of a random variable taking on a specific value.

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