Table of Contents
- 1 Are continuous random variables infinite?
- 2 Is entropy always finite?
- 3 What does a continuous random variable assume?
- 4 Can continuous variables be finite?
- 5 Is entropy an invariant?
- 6 Can differential entropy be zero?
- 7 Why the probability that a continuous random variable equals some value is always zero?
Are continuous random variables infinite?
A continuous random variable is a random variable where the data can take infinitely many values. For example, a random variable measuring the time taken for something to be done is continuous since there are an infinite number of possible times that can be taken.
Is entropy always finite?
Entropy in information theory is directly analogous to the entropy in statistical thermodynamics. For a continuous random variable, differential entropy is analogous to entropy.
Can differential entropy be infinite?
It’s not hard to verify that its differential entropy is infinite. It grows quite slowly though (approx. logarithmically).
What does a continuous random variable assume?
A continuous random variable may assume any value in an interval on the real number line or in a collection of intervals. The expected value, or mean, of a random variable—denoted by E(x) or μ—is a weighted average of the values the random variable may assume.
Can continuous variables be finite?
Continuous variable is infinite and uncountable. Methods of calculus are often used in problems in which the variables are continuous, for example in continuous optimization problems. In statistical theory, the probability distributions of continuous variables can be expressed in terms of probability density functions.
Can discrete random variable be infinite?
A discrete random variable is one that can assume only a finite, or countably infinite, number of distinct values.
Is entropy an invariant?
Properties of differential entropy Differential entropy is in general not invariant under arbitrary invertible maps.
Can differential entropy be zero?
If you do the differential entropy h of this, you will find it is zero since ln(1)=0 and moreover in the appropriate limit 0ln(0) “equals” 0.
Is random variable discrete or continuous?
A discrete variable is a variable whose value is obtained by counting. A continuous variable is a variable whose value is obtained by measuring. A random variable is a variable whose value is a numerical outcome of a random phenomenon. A discrete random variable X has a countable number of possible values.
Why the probability that a continuous random variable equals some value is always zero?
The probability of a specific value of a continuous random variable will be zero because the area under a point is zero.