Calculating the Variance for X^2: How to Find the Correct Solution

  • Thread starter Addez123
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In summary, the conversation discusses calculating the variance for a probability density function fx(x) = x^2 on the interval [0,1]. The correct answer is 4/45, obtained by calculating u = 1/3 and using the formula for variance, E(X^2) - (E(X))^2. The conversation also clarifies that g(x) = x^2 and fx(x) = 1, and discusses the process of computing the variance.
  • #1
Addez123
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Homework Statement
X is equally distributed along the intervall [0,1]
Calculate variance for X^2
Relevant Equations
Variance:
$$\int (x-u)^2*fx(x) dx$$
At first I assumed u to be 1/2 since X is equally distributed along 0-1.
$$\int (x-1/2)^2*x^2 dx = 1/30$$
The correct answer should be 4/45.

I would calculate the u but I think I do it wrong.
If fx(x) = x^2 then what is g(x)?

fx is the probability density function, which is the x^2 they supplied, right?
g(x) i have no real definition for.
 
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  • #2
Addez123 said:
fx(x) = x^2
This is not the pdf of a uniform distribution on [0,1]
 
  • #3
Orodruin said:
This is not the pdf of a uniform distribution on [0,1]
So g(x) = x^2, and fx(x) = 1?
Because then you get u = 1/3rd and variance = 1/9th :/
 
  • #4
Addez123 said:
So g(x) = x^2, and fx(x) = 1?
Because then you get u = 1/3rd and variance = 1/9th :/
Show how you are computing the variance.
(I think it is easiest to use E(X2)-(E(X))2.)
 
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  • #5
$$\int (x-1/3)^2 * 1 dx$$
from 0 to 1
EDIT: It should say x^2 since we're donig variance for v(x^2) not v(x). That gives the correct solution.
 
Last edited:
  • #6
Addez123 said:
$$\int (x-1/3)^2 * 1 dx$$
from 0 to 1
EDIT: It should say x^2 since we're donig variance for v(x^2) not v(x). That gives the correct solution.
Yes.
 

1. What is the formula for finding the variance of X^2?

The formula for finding the variance of X^2 is Var(X^2) = E[(X^2)^2] - (E[X^2])^2.

2. How do you interpret the variance of X^2?

The variance of X^2 measures the spread of the values of X^2 around its mean. A higher variance indicates a wider range of values, while a lower variance indicates a narrower range of values.

3. Can the variance of X^2 be negative?

No, the variance of X^2 cannot be negative. It is always a non-negative value, since it is calculated by squaring the differences between each value of X^2 and its mean.

4. What is the relationship between the variance of X and the variance of X^2?

The variance of X^2 is equal to the square of the variance of X. In other words, Var(X^2) = (Var(X))^2. This means that the variance of X^2 will always be a larger value than the variance of X.

5. How is the variance of X^2 affected by changes in the values of X?

The variance of X^2 is affected by changes in the values of X in the same way as the variance of X. If the values of X are spread out, the variance of X^2 will also be larger. If the values of X are close together, the variance of X^2 will be smaller.

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