Characteristic function and preimage?

In summary, the characteristic function, denoted as χs, is defined as 1 if x is in subset S and 0 if x is not in subset S. For the preimage of the set of all rational numbers, it is the set of all numbers in S and the complement of S, which is the set of all real numbers. Similarly, for the preimage of the interval (0, ∞), it is also the set of all numbers in S and the complement of S, which are all real numbers.
  • #1
SMA_01
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Characteristic function and preimage?

Homework Statement



Let S be a nonempty subset of ℝ.

Define χs= { 1 if x is in S and 0 if x is not in S

Determine χs-1(Q) [where Q=set of all rational numbers]

and χs-1((0,∞))

We haven't really dealt much with this function, and I really don't know how to go about doing this. I'm guessing for Q it will be all x in S such that f(x)=Q? Is that right?

Any help is appreciated,

Thanks.
 
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  • #2


Then go back an review the definitions! Once you know the definitions, this problem is trivial.

Your function, "[itex]X_S[/itex]" (strictly speaking, "[itex]\chi_s[/itex]", the Greek letter "chi") is defined to be 1 if x is in S, 0 if not. In other words, the only possible value of x is 0 or 1, both of which are rational numbers, but only 1 is in [itex](0, \infty)[/itex].
 
  • #3


Thank you, so for the rationals, the preimage of chi sub s is the set of all numbers in S and the complement of S, i.e. the set of all reals. Is that correct?
 
  • #4


SMA_01 said:
Thank you, so for the rationals, the preimage of chi sub s is the set of all numbers in S [STRIKE]and[/STRIKE] or in the complement of S, i.e. the set of all reals. Is that correct?

Yes.

(There are no numbers which are both in set S and in the compliment of set S.)
 

FAQ: Characteristic function and preimage?

1. What is a characteristic function?

A characteristic function is a mathematical function that is used to describe the distribution of a random variable. It maps the probability of different outcomes onto a continuous number line, with a value of 1 representing the most probable outcome and a value of 0 representing an impossible outcome.

2. How is a characteristic function related to a probability distribution?

A characteristic function is related to a probability distribution through the inverse Fourier transform. By taking the inverse Fourier transform of the characteristic function, we can obtain the probability density function (PDF) of the random variable, which describes the relative likelihood of different outcomes.

3. What is the importance of the characteristic function in statistics?

The characteristic function is important in statistics because it provides a convenient way to analyze and manipulate probability distributions. It allows us to easily calculate moments, find the distribution of sums of independent random variables, and perform other operations that would be difficult or impossible using the PDF or cumulative distribution function (CDF) alone.

4. What is the preimage of a characteristic function?

The preimage of a characteristic function is the set of all points or values in the domain that map to a particular value in the range. In other words, it is the set of all possible outcomes that could result in a given probability value in the characteristic function.

5. How is the preimage used in probability theory?

In probability theory, the preimage is used to calculate probabilities of events by taking the inverse characteristic function of the probability measure. It is also used in statistical inference to find the distribution of a random variable based on a given set of data or observations.

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