I'm taking a course on probability theory. This is how my teacher has defined a uniform random variable:
Let $X$ be a random variable. We say $X$ is uniformly distributed in $(0,1)$ if for every $a,b \in\mathbb R$,
$P(a < X < b) =\lambda[(a,b)\cap (0,1)]$, where $\lambda$ is Lebesgue measure
I'm having trouble in understanding and applying this definition.
For example, I was doing the following question:
Let $U$ be a uniform random variable on $[0,1]$. Let $X=U^2$. Find distribution function of $X$.
What I tried:
$$\{X \leq x\} = \{U^2 \leq x\} = \{-\sqrt x \leq U \leq \sqrt x\}$$
So, $F(x)= P\{X \leq x\} = \lambda([-\sqrt x ,\sqrt x\,] \cap [0,1])$
Is this right?
It's ok, but since you know that $\Pr(U>0)=1$, I'd just write $0\le U \le \sqrt x$. Then of course, simplify the expression $\lambda([0,\sqrt x\,] \cap [0,1])$.