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)
$x _ { 1 } =$ Microprocessor SPEED (measured in megahertz)
(Values in sample range from 10 to 40 )
$x _ { 2 } =$ 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:
$\begin{array}{lrrrrr} & {\text { Analysis of Variance }} \\\text { SOURCE } & \text { DF } & \text { SS } & \text { MS } & \text { F VALUE } & \text { PROB > F } \\\text { MODEL } & 2 & 34593103.008 & 17296051.504 & 19.018 & 0.0001 \\\text { ERROR } & 57 & 51840202.926 & 909477.24431 & & \\\text { CTOTAL } & 59 & 86432305.933 & & &\end{array}$


$\begin{array}{llll}\text { ROOT MSE } & 953.66516 & \text { R-SQUARE } & 0.4002 \\\text { DEP MEAN } & 3197.96667 & \text { ADJ R-SQ } & 0.3792 \\\text { C.V. } & 29.82099 & &\end{array}$


Test to determine if the model is adequate for predicting the price of a computer. Use $\alpha =$ $.01$ .