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Retail Price Data for N = 60 Hard Disk Drives y=y =

question 14

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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=y = Retail PRICE (measured in dollars)
x1=x _ { 1 } = Microprocessor SPEED (measured in megahertz)
(Values in sample range from 10 to 40 )
x2=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:

 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:       Identify and interpret the estimate for the SPEED  \beta -coefficient,  \hat { \beta } _ { 1 } . A)   \hat { \beta } _ { 1 } = 3.57 ; For every  \$ 1  increase in PRICE, we estimate SPPED to increase by about 4 megahertz, holding CHIP fixed. B)   \hat { \beta } _ { 1 } = 3.57 ; For every 1 -megahertz increase in SPEED, we estimate PRICE to increase  \$ 3,57 , holding CHIP fixed.  C)   \hat { \beta } _ { 1 } = 105 ; For every  \$ 1  increase in PRICE, we estimate SPEED to increase 105 megahertz, holding CHIP fixed. D)   \hat { \beta } 1 = 105 ; For every 1 -megahertz increase in SPEED, we estimate PRICE (y)  to increase  \$ 105 , holding CHIP fixed.



Identify and interpret the estimate for the SPEED β\beta -coefficient, β^1\hat { \beta } _ { 1 } .


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