What is the correct probability for P(3<X<4|X>1)?

Click For Summary

Discussion Overview

The discussion revolves around calculating the conditional probability P(31) for a continuous random variable X defined on a non-uniform density function f(x) = C*(1+x) over the interval from 2 to 5. Participants explore the integration process to determine the normalization constant C and the probabilities involved.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant calculates the normalization constant C as 2/27 using integration from 2 to 5.
  • Another participant confirms the value of C and agrees on the numerator for the conditional probability, stating that P([31]) = P(3
  • There is a challenge regarding the denominator, where one participant claims that the calculation of P(X>1) is incorrect, suggesting that it should equal 1 instead of 32/27 due to the bounds of the distribution.
  • One participant notes that the book's answer of 9/27 is equivalent to 1/3, raising questions about the presentation of the answer.
  • A later reply acknowledges a mistake in calculations, indicating a realization of an oversight in the reasoning process.

Areas of Agreement / Disagreement

Participants generally agree on the value of C and the numerator for the conditional probability. However, there is disagreement regarding the calculation of the denominator, leading to differing interpretations of the final probability result.

Contextual Notes

Participants note that any probability must be between 0 and 1, which raises concerns about the validity of certain calculations. There are also references to specific integration steps and the implications of the bounds of the random variable.

Yankel
Messages
390
Reaction score
0
Hello, I have this question, which I think I solve correctly, but I am getting the wrong answer.

X represent the point that the computer chooses on a scale of 2 to 5 (continuous scale) in a non-uniform way using the density:

f(x)=C*(1+x)

what is the probability P(3<X<4|X>1) ?

I solved the integral from 2 to 5 to find that C=2/27

Then using this value I did conditional probability P(3<X<4)/P(X>1). The nominator was 1/3 and the denominator was 32/27, my final result is then 9/32. The answer I have with the question is 9/27. Which one is wrong then ? Can you assist me please? Thank you in advance !
 
Physics news on Phys.org
I have

$$\displaystyle c\times \int_2^5 x+1 ~dx = 1$$

$$\displaystyle c\times \left[ \frac{x^2}{2}+x\right]_2^5 = 1$$

$$\displaystyle c\times \left(\left[ \frac{5^2}{2}+5\right]-\left[ \frac{2^2}{2}+2\right]\right) = 1$$

$$\displaystyle c\times \left(\left[ 12.5+5\right]-\left[ 2+2\right]\right) = 1$$

$$\displaystyle c\times \left(\left[ 17.5\right]-\left[ 4\right]\right) = 1$$

$$\displaystyle c = \frac{1}{13.5} = \frac{2}{27}$$
 
Yankel said:
Hello, I have this question, which I think I solve correctly, but I am getting the wrong answer.

X represent the point that the computer chooses on a scale of 2 to 5 (continuous scale) in a non-uniform way using the density:

f(x)=C*(1+x)

what is the probability P(3<X<4|X>1) ?

I solved the integral from 2 to 5 to find that C=2/27

Then using this value I did conditional probability P(3<X<4)/P(X>1). The nominator was 1/3 and the denominator was 32/27, my final result is then 9/32. The answer I have with the question is 9/27. Which one is wrong then ? Can you assist me please? Thank you in advance !

Hi Yankel,

I got the same thing for $C$ and the same numerator since $P([3<X<4] \cap [X>1])=P(3<X<4)$. For the denominator though it seems like you used this integral:
$$ \frac{2}{27} \int_{1}^{5} (1+x) \, dx = \frac{32}{27}$$
Remember though that any probability must be between 0 and 1, so this isn't a valid answer. The small mistake comes from the fact that $P(X<2)=0$ and $P(X>5)=0$, so $P(X>1)=P(2<X<5)=1$. For some reason the book chose to write the answer as 9/27 instead of 1/3, but those are equivalent answers. :)
 
Oh...how did I miss this...typing numbers without thinking (Doh)

thanks !
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 10 ·
Replies
10
Views
2K