The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA. ŷ = -1.4053 + .0235x1 + .0049x2 where ¤1 = high-school grade point average xz = SAT mathematics score y = final college grade point average Round your answers to 4 decimal places. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
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ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
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Chapter3: Straight Lines And Linear Functions
Section3.4: Linear Regression
Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the
student's SAT mathematics score and high-school GPA.
ŷ = -1.4053 + .0235¤1 + .0049x2
where
a1 = high-school grade point average
x2 = SAT mathematics score
y = final college grade point average
Round your answers to 4 decimal places.
a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.
ANOVA
df
MS
F
Significance F
Regression
2.
1.7621
0.88105
Residual
7
.1179
0.01685
Total
1.88
Coefficients
Standard Error
t Stat
P-value
Intercept
-1.4053
0.4848
0.24
X1
0.0235
0.0087
0.0302
X2
0.0049
0.0011
0.003
Transcribed Image Text:The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA. ŷ = -1.4053 + .0235¤1 + .0049x2 where a1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average Round your answers to 4 decimal places. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. ANOVA df MS F Significance F Regression 2. 1.7621 0.88105 Residual 7 .1179 0.01685 Total 1.88 Coefficients Standard Error t Stat P-value Intercept -1.4053 0.4848 0.24 X1 0.0235 0.0087 0.0302 X2 0.0049 0.0011 0.003
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