I have a very very basic question on the CDF and limits

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In summary, the function G is not right continuous nor has a left limit at x=0, while H is right continuous and has a left limit at x=1.
  • #1
Roni1985
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Homework Statement



1. For a random variable X, the function F defined by
F(x) = P(X <= x),−inf < x < inf
is called the cumulative distribution function of X. A property of every distribution function F is that
it is right continuous with left limits.
For the following functions, determine if they are right continuous and/or have left limits at the
indicated values. (A “yes” or “no” answer is insufficient. Justify your answers or no credit will be
given.)
(a) at x = 0 and x = 1 for G(x) = |x|/x .
(b) at x = 0 and x = 1 for H(x) = arctan(x).


Homework Equations



(a) at x = 0 and x = 1 for G(x) = |x|/x .
(b) at x = 0 and x = 1 for H(x) = arctan(x).

The Attempt at a Solution



Well, if we look at 'a', I was trying to find the limit when x->0+ and limit when x->0-. I am getting -1 and 1
but the function is not defined at x=0.
and it's not right continuous nor left continuous, and it has right and left limits, correct?

OR I don't get the question.

Can somebody tell me what I need to do here or lead me to the correct way ??

Thanks in advance,
Roni.
 
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  • #2
That sounds fine to me. Except I would say lim 0+ of |x|/x is 1. It's the limit as x->0 from the positive direction, right? OR I don't get the question. Or I misunderstand your notation.
 
  • #3
Dick said:
That sounds fine to me. Except I would say lim 0+ of |x|/x is 1. It's the limit as x->0 from the positive direction, right? OR I don't get the question. Or I misunderstand your notation.

yes, that's what I meant, from the positive side it's 1 and from the negative side it's -1.

So, this equation is not a CDF ? as far as I understand, a CDF is right continuous and has left limits . But this one is neither right nor left continuous and has left and right limits, right ?

now what about arctan(x) ?

As far as I know, arctan is continuous from -inf to inf. So, it's right continuous but doesn't have left limit, right ? So it's not a CDF either?
If so, why did the professor mention the CDF properties ? o_O
 
  • #4
Uh, don't know. Maybe the question isn't really about CDF's but about concepts of continuity and limits and mentioning CDFs was just a motivation. As far as I know, a good CDF f(x) has the property that lim x->-infinity is 0 and lim x->infinity is 1. Neither of those functions is good in that respect.
 
  • #5
Dick said:
Uh, don't know. Maybe the question isn't really about CDF's but about concepts of continuity and limits and mentioning CDFs was just a motivation. As far as I know, a good CDF f(x) has the property that lim x->-infinity is 0 and lim x->infinity is 1. Neither of those functions is good in that respect.

I see, I guess you are right .
Thank you very much for your help :)
 

Related to I have a very very basic question on the CDF and limits

1. What is the CDF and how does it relate to limits?

The CDF, or cumulative distribution function, is a function that shows the probability that a random variable is less than or equal to a certain value. It is related to limits because as the limit of the CDF approaches a certain value, it represents the probability of the random variable being less than or equal to that value.

2. How is the CDF calculated?

The CDF is calculated by taking the integral of the probability density function (PDF) of a random variable. The PDF represents the probability of the random variable taking on a certain value, while the CDF represents the probability of the random variable being less than or equal to that value.

3. Can the CDF be used to calculate probabilities for continuous random variables?

Yes, the CDF can be used for both continuous and discrete random variables. For continuous random variables, the CDF is a smooth curve, while for discrete random variables, the CDF is a step function.

4. What is the relationship between the CDF and the inverse CDF?

The inverse CDF, also known as the quantile function, is the function that returns the value of the random variable at a certain probability. It is the inverse of the CDF, which takes a value of the random variable and returns the probability. Together, they can be used to find the probability of a random variable being within a certain range.

5. How is the CDF used in hypothesis testing?

In hypothesis testing, the CDF is used to determine the p-value, which is the probability of obtaining a result at least as extreme as the observed result, assuming the null hypothesis is true. The CDF is used to find the area under the curve of the null distribution, which is then compared to the observed result to determine the significance of the result.

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