Author Question: As part of a study at a large university, data were collected on n = 224 freshmen computer science ... (Read 108 times)

anjilletteb · **on:** Feb 14, 2020

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:

Parameter Estimates

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.

samiel-sayed · **Reply #1 on:** Feb 14, 2020

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