Retail Price Data For $n = 60$ Hard Disk Drives Were Recently Reported in a Computer Magazine

Retail price data for $n = 60$ hard disk drives were recently reported in a computer magazine. Three variables were recorded for each hard disk drive:
$y =$ Retail PRICE (measured in dollars)
$\mathrm { x } _ { 1 } =$ Microprocessor SPEED (measured in megahertz)
(Values in sample range from 10 to 40 )
$\mathrm { x } _ { 2 } = \mathrm { CHIP }$ size (measured in computer processing units)
(Values in sample range from 286 to 486 )

A first-order regression model was fit to the data. Part of the printout follows:

$\begin{array} { r r r r r r r r r } \hline& & & \text { Dep Var } & \text { Predict } & \text { Std Err } & \text { Lower 95\% } & \text { Upper 95\% } & \\\text { OBS } & \text { SPEED } & \text { CHIP } & \text { PRICE } & \text { Value } & \text { Predict } & \text { Predict } & \text { Predict } & \text { Residual } \\& & & & & & & & \\1 & 33 & 386 & 5099.0 & 4464.9 & 260.768 & 3942.7 & 4987.1 & 634.1\\\hline\end{array}$


Interpret the $95 \%$ prediction interval for $y$ when $x _ { 1 } = 33$ and $x _ { 2 } = 386$ .