Question

Help with this statistics problem please.

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) Afirst-order model was fitted to the data. A 95% confidence interval for B1 is 0.06,.22). Interpret this result. We are 95% confident that the mean GPA of all CS freshmen after three semesters falls between .06 and .22. 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. 95% of the GPAs fall within .06 to .22 of their true values. 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.

Answer 1

Correct option:

We are 95% confident that a CS freshma's GPA increases by an amount between .06 and .22 for every 1 - point increase in average HS math grade, holding x2-x5 constant.

Explanation:

Given:

95% Confidence Interval for is (0.06, 0.22)

B1

is the slope coefficient of the Independent Variable: X₁= average High School grade in mathematics (HSM).

B1

95% Confidence Interval for : (0.06, 0.22) is interpreted as follows:

B1

We are 95% confident that a CS freshma's GPA increases by an amount between 0.06 and 0.22 for every 1 - point increase in average HS math grade, holding x2, x3, x4 and x5 constant