The probability density function (pdf) is given as \(f(x) = 0.
01\) for \(0 \le x \le 100\), and \(f(x) = 0\) otherwise.
This is a uniform distribution over the interval [0, 100].
The mean (or expected value) \(E[X]\) of a continuous random variable X with pdf \(f(x)\) is calculated as:
$$ E[X] = \int_{-\infty}^{\infty} x f(x) dx $$
For this uniform distribution:
$$ E[X] = \int_{0}^{100} x (0.
01) dx $$
$$ E[X] = 0.
01 \int_{0}^{100} x dx $$
$$ E[X] = 0.
01 \left[ \frac{x^2}{2} \right]_{0}^{100} $$
$$ E[X] = 0.
01 \left( \frac{100^2}{2} - \frac{0^2}{2} \right) $$
$$ E[X] = 0.
01 \left( \frac{10000}{2} \right) = 0.
01 \times 5000 = 50 $$
The mean is 50.
0.
Alternatively, for a uniform distribution over the interval [a, b], the mean is simply the midpoint of the interval: \((a+b)/2\).
Here, \(a=0\) and \(b=100\), so the mean is \((0+100)/2 = 50\).