We have a measurement which has mean $\mu$ and variance $\sigma^2$ = 25. Let $\bar{X}$ be average of $\textit{n}$ such independent measurements.
How large should $\textit{n}$ be in so that $P(|\bar{X} - \mu| < 1) = 0.95$
This is what I got so far:
$P(\frac{\sqrt{n} * (-1)}{\sqrt{25}} < \frac{\bar{X} - \mu}{\sqrt{25}} < \frac{\sqrt{n} * (1)}{\sqrt{25}}) = 0.95$
Yielding
$\Phi(\frac{\sqrt{n}}{\sqrt{25}}) - \Phi(-\frac{\sqrt{n}}{\sqrt{25}}) = 0.95$
And this is when I get lost. How do I remove the $\Phi$ so to find $n$? I tried to find the z-value corresponding to 0.95, which is 1.65, but that did not help.
The correct result is $n=96$ (it is an exercise from Rice, third edition, problem 5/17).