Just want to know if someone can check my work on this.
Individual claim sizes may be modeled by a uniform distribution function on the interval $[1000, 5000]$. Eighty claims are examined. Assume claims are independent.
What is the approximate probability that total claims will be between $250,000$ and $300,000$?
Here's what I did: $$\mu = {(a+b)\over2}=3000$$ $$\sigma^2={(b-a)^2\over12} = {4000^2\over12}={16000000\over12}$$ $$\sigma = \sqrt{\sigma^2}=\sqrt{16000000\over12}=1154.7$$
New $\mu = 3000*80 = 240,000$ and new $\sigma = 1154.7*80=92376.04307$
So we want $$Pr({10000\over92376.04307}<z<{60000\over92376.04307})$$ $$=P(z<.6495)-1+P(z<.108)$$ I end up getting a negative number which isn't right, what am I missing?
You have a sum of 80 independent random variables. Let´s say $Y=\sum\limits_{i=1}^{80}X_i$, where $X_i\sim U(1000,5000)$
Then $\mu_Y=80\cdot 3000$. And the variance of the sum of independent random variables is equal to the sum of the variances.
$Var\left(\sum\limits_{i=1}^n X_i\right)=\sum_{i=1}^n Var(X_i)$
Therefore $Var(Y)=80\cdot \frac{4000^2}{12}$
Applying central limit theorem
$$P(250,000\leq Y\leq300,000)\approx\Phi \left( \frac{300,000-240,000}{\sqrt{80\cdot \frac{4000^2}{12}}}\right)-\Phi \left( \frac{250,000-240,000}{\sqrt{80\cdot \frac{4000^2}{12}}} \right)$$ $$=\Phi(5.81)-\Phi(0.968)=1-0.8334=0.1666=16.66\%$$