μ = 1000 (mean of exponential density of individual variable )
n = 100 (number of light bulbs)
The density of minimum value among n independent random variables with an exponential density has mean \(\frac{μ}{n}\),
So the mean of the minimum value (first bulb to burn out) is:
μ = 1000
n = 100
print(μ/n)
## [1] 10
\(fz(z) = (\frac{1}{2})e^{-λ|z|}\) can be rewritten as: \[ fz(z) = \begin{cases} (\frac{1}{2})e^{-λ|z|}, z \geq 0\\ (\frac{1}{2})e^{λ|z|}, z < 0 \end{cases} \]
Since \(X_1\) and \(X_2\) have exponential density, their PDF is:
\[ fx(x_1) = fx(x_2) = \begin{cases} λe^{-λx}, x \geq 0\\ 0, otherwise \end{cases} \]
So the combined density is \(λ^2e^{-λ(χ_1 + χ_2)}\)
If \(z = x_1 - x_2\) then \(x_1 = z + x_2\) \(=>\)
If \(z \geq 0\), then \(x_1 = (z + x_2) \geq 0\) and
\(fz(z) = \int_{z}^{∞} λ^2e^{-λ(z + 2x_2)}, dx_2 = \frac{1}{2}λe^{-λz}\)
If \(z < 0\), then \(x_1 = (z + x_2) > 0\) and
\(fz(z) = \int_{0}^{∞} λ^2e^{λ(z + 2x_2)}, dx_2 = \frac{1}{2}λe^{λz}\)
then \[ fz(z) = \begin{cases} (\frac{1}{2})e^{-λz}, z \geq 0\\ (\frac{1}{2})e^{λz}, z < 0 \end{cases} \]
Chebyschev inequality states:
\(P(| X - μ | \geq kσ ) \leq \frac{1}{k^2}\)
\(μ\) is given as 10, with \(σ^2\) as \(\frac{100}{3}\), so \(σ = \frac{10}{\sqrt(3)}\)
Thus,
so, \(\frac{1}{k^2} = 8.338\)
Since the upper bound cannot exceed 1, the upper bound is 1.
so, \(\frac{1}{k^2} = 1.33334\)
Since the upper bound cannot exceed 1, the upper bound is 1.
so, \(\frac{1}{k^2} = 0.41152\)
The upper bound is 0.41152.
so, \(\frac{1}{k^2} = 0.08333\)
The upper bound is 0.08333.