Question 1
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)
x1 = Microprocessor SPEED (measured in megahertz)
(Values in sample range from 10 to 40)
x2 = 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 of
β2.
Question 2
As part of a study at a large university, data were collected on
n = 224 freshmen computer science (CS) majors in a particular year. The researchers were interested in modeling
y, a student's grade point average (GPA) after three semesters, as a function of the following independent variables (recorded at the time the students enrolled in the university):
x1 = average high school grade in mathematics (HSM)
x2 = average high school grade in science (HSS)
x3 = average high school grade in English (HSE)
x4 = SAT mathematics score (SATM)
x5 = SAT verbal score (SATV)
A first-order model was fit to data.
A 95% confidence interval for
β1 is (.06, .22). Interpret this result.
◦ We are 95% confident that a CS freshman's GPA increases by an amount between .06 and .22 for every 1-point increase in average HS math grade, holding
x2 -
x5 constant.
◦ We are 95% confident that the mean GPA of all CS freshmen after three semesters falls between .06 and .22.
◦ 95% of the GPAs fall within .06 to .22 of their true values.
◦ We are 95% confident that a CS freshman's HS math grade increases by an amount between .06 and .22 for every 1-point increase in GPA, holding
x2 -
x5 constant.
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