Probabiltity space and random variables

[rosh300]

Homework Statement

\Omega is a set of points \omega ; C_{i} i = 1, 2, ... 7 are subsets of \Omega;
and (\Omega, F, P) = (B_{i}, i/10, i = 1, 2, 3, 4) is a probability modal
with B_{1} = C_{1} \cup C_{7}, B_{2} = C_{2} \cup C_{6}, B_{3} = C_{3} \cup C_{5} and B_{4} = C_{4}.
State which of the following functions X:\Omega \rightarrow R are random variables defined on (\Omega, F, P) and derive the distributions.

(i)X(\omega) = -3 for \omega \in C_{1} \cup C_{7} \cup C_{3} \cup C_{5} with X(\omega) = 2 otherwise

(ii) X(\omega) = 1 for \omega \in C_{1} \cup C_{7}, X(\omega) = 2 for \omega \in C_{3} \cup C_{4} and X(\omega) = 2 for \omega \in C_{2} \cup C_{5} \cup C_{6}

(iii)X(\omega) = (v-4)^{2} for \omega \in C_{v}, v = 1, 2, ... 7

Homework Equations

definition of random varibale, probability space

The Attempt at a Solution

(i) random variable
Distrubution:
(-\infty, -3) = 0
[-3, 2) = 1/10 + 3/10 = 2/5
[2,\infty) = 1

(ii) not a random variable

(iii) random variable
distrubution:
(-\infty, 0) = 0,
[0, 1) = 4/10
[1, 4) = 7/10
[4, 9) = 9/10
[9, \infty] = 1

 

[member38644]

A probability space is a mathematical construct used to model random experiments or processes. It consists of three parts: a sample space (\Omega) which is the set of all possible outcomes of the experiment, a sigma-algebra (F) which is a collection of subsets of \Omega, and a probability measure (P) which assigns a probability to each event in the sigma-algebra. Random variables are functions defined on the sample space that assign a numerical value to each outcome. They allow us to analyze the probabilities of different events and outcomes in a probabilistic experiment.

In the given problem, \Omega is the set of points \omega, C_{i} are subsets of \Omega, and ( \Omega, F, P) is a probability model with B_{i} defined as the union of certain subsets of \Omega. This means that the probability measure P assigns a probability of i/10 to the event B_{i}.

For the first function X(\omega), we can see that it assigns a value of -3 to all outcomes in the sets C_{1}, C_{3}, C_{5}, and C_{7}, and a value of 2 to all other outcomes. This is a valid random variable since it assigns a numerical value to each outcome in the sample space. The distribution can be derived by considering the probabilities assigned to each set in the sample space.

For the second function X(\omega), it is not a valid random variable since it assigns different values to the same outcomes in the sample space. For example, it assigns a value of 1 to outcomes in both C_{1} and C_{7}, and a value of 2 to outcomes in both C_{3} and C_{4}. This violates the definition of a random variable.

The third function X(\omega) assigns the square of the index of the subset in which the outcome \omega belongs to. This is also a valid random variable, and the distribution can be derived by considering the probabilities assigned to each subset in the sample space.

Overall, a probability space and random variables are important concepts in probability theory that allow us to analyze and make predictions about the outcomes of random experiments.