Proof: Quantile Function Property

In summary, the problem is asking to prove that for a general random variable X, the quantile function F-1 has properties that are analogous to the properties of a c.d.f. The values x0 and x1 are the greatest lower bound and least upper bound respectively on the set of numbers c and d such that Pr(X≤c) > 0 and Pr(X≥d) > 0. This is because as p approaches 0, F-1(p) approaches the smallest x-value for which Pr(X≤x) = 0, and as p approaches 1, F-1(p) approaches the largest x-value for which Pr(X≥x) = 0. To prove this,
  • #1
icestone111
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Homework Statement


F-1 is the quantile function of a general random variable X and has the following property that is analogous to the property of the c.d.f.
Prove: Let x0 = limp→0,p>0 F-1(p) and x1 = limp→1,p<1 F-1(p). Then x0 equals the greatest lower bound on the set of numbers c such that Pr(X≤c) > 0, and x1 equals the least upper bound on the set of numbers d such that Pr(X≥d) > 0.

The Attempt at a Solution


I'm not too sure where to begin with proving this problem...
My interpretation of the problem is that x0 and x1 are the (lowest?) lower and (greatest?) upper bounds such that Pr(X=x) > 0.
 
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  • #2
Since F-1 is the quantile function of a general random variable X, this means that F-1(p) is the x-value such that Pr(X≤x) = p. Therefore, a limiting value of p→0 would result in an x-value such that Pr(X≤x) = 0 and a limiting value of p→1 would result in an x-value such that Pr(X≥x) = 0. Thus, x0 and x1 are the greatest lower bound and least upper bound respectively. Is this correct? If so, how would I go about proving it?
 

FAQ: Proof: Quantile Function Property

What is the quantile function property?

The quantile function property is a mathematical property that relates to the probability distribution of a random variable. It describes the relationship between the cumulative distribution function (CDF) and the quantile function, which is the inverse of the CDF.

How is the quantile function property used in statistics?

The quantile function property is used to calculate the probability of a specific outcome or range of outcomes for a random variable. It is also used to generate random numbers from a specific distribution, which is important in many statistical analyses.

Can the quantile function property be applied to any distribution?

Yes, the quantile function property can be applied to any continuous probability distribution. However, it may not be applicable to discrete distributions, as they do not have a continuous CDF.

What is the relationship between the quantile function property and the central limit theorem?

The quantile function property is closely related to the central limit theorem, which states that the sample mean of a large number of independent and identically distributed random variables will follow a normal distribution. The quantile function property is used to calculate the quantiles of this normal distribution.

How is the quantile function property used in hypothesis testing?

The quantile function property is used in hypothesis testing to determine the critical values for a specific level of significance. These critical values are compared to the test statistic to determine if the null hypothesis should be rejected or not.

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