Is X(\omega) = \frac{1}{\omega} a Random Variable?

In summary, Wayne asked if X(\omega) = \frac{1}{\omega} is a bounded random variable on the probability space (\Omega, \mathcal{F},P) = ([0,1],\mathcal{B}([0,1]),\lambda), with \lambda as Lebesgue measure. The answer is no, as there is no set of measure 0 on the compliment of which the function is bounded.
  • #1
wayneckm
68
0
Hello all,

I have the following question:

Assume [tex](\Omega, \mathcal{F},P) = ([0,1],\mathcal{B}([0,1]),\lambda)[/tex], where [tex]\lambda[/tex] is Lebesgue mesure, so is [tex]X(\omega) = \frac{1}{\omega}[/tex] a random variable defined on this probability space?

If yes, then can I say that [tex]X[/tex] is bounded a.s. because the set for unboundedness is [tex]{0}[/tex] which is of measure 0?

Thanks.

Wayne
 
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  • #2
wayneckm said:
Hello all,

I have the following question:

Assume [tex](\Omega, \mathcal{F},P) = ([0,1],\mathcal{B}([0,1]),\lambda)[/tex], where [tex]\lambda[/tex] is Lebesgue mesure, so is [tex]X(\omega) = \frac{1}{\omega}[/tex] a random variable defined on this probability space?

If yes, then can I say that [tex]X[/tex] is bounded a.s. because the set for unboundedness is [tex]{0}[/tex] which is of measure 0?

Thanks.

Wayne

No.

Because there is no set of measure 0 on the compliment of which the function is bounded.
 

FAQ: Is X(\omega) = \frac{1}{\omega} a Random Variable?

What is a random variable?

A random variable is a numerical representation of a random event or outcome. It can take on various values depending on the probability of the event occurring.

How is a random variable defined?

A random variable is defined as a function that maps each outcome of a probability experiment to a numerical value.

What is the significance of X(\omega) = \frac{1}{\omega} in a random variable?

The function X(\omega) = \frac{1}{\omega} is a mathematical representation of a continuous random variable. It describes the probability distribution of the variable and can be used to calculate probabilities and expectations.

Is X(\omega) = \frac{1}{\omega} a discrete or continuous random variable?

X(\omega) = \frac{1}{\omega} is a continuous random variable. This means that it can take on any real value within a given range. In contrast, a discrete random variable can only take on specific, separate values.

How is the probability distribution of X(\omega) = \frac{1}{\omega} determined?

The probability distribution of X(\omega) = \frac{1}{\omega} is determined by the values it can take on and the corresponding probabilities of each value occurring. This can be represented graphically with a probability density function, which shows the relative likelihood of each value occurring.

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