Independent solution

How to solve this Central Limit Theorem question

Answer in brief

The aggregate has mean 3,000,000 and standard deviation 50,000 times the square root of 60. A central-limit approximation gives an upper-tail probability of 0.09835, so the nearest listed value is choice A.

Setup

Setup

Let S be the aggregate of the 60 independent exponential loss variables.

S=i=160XiS=\sum_{i=1}^{60}X_i
E[S]=60(50000)=3000000E[S]=60(50000)=3000000

Model

Model

An exponential variable has standard deviation equal to its mean. Independence makes the component variances additive, and the central limit theorem supplies a normal approximation.

SD(S)=5000060=387298.3346\operatorname{SD}(S)=50000\sqrt{60}=387298.3346\ldots
S ˙ N ⁣(3000000,60(50000)2)S\ \dot\sim\ N\!\left(3000000,\,60(50000)^2\right)

Compute

Compute

Standardize the aggregate threshold and evaluate the upper standard-normal tail.

z=350000030000005000060=1060=1.2909944487z=\frac{3500000-3000000}{50000\sqrt{60}}=\frac{10}{\sqrt{60}}=1.2909944487\ldots
Pr(S>3500000)1Φ(1.2909944487)=0.0983528012\Pr(S>3500000)\approx1-\Phi(1.2909944487)=0.0983528012\ldots

Answer

Answer

The approximation is closest to 0.10.

0.10(A)\boxed{0.10\quad\text{(A)}}