please assist 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 = -1.41 + 0.0235a1 + 0.00486x2where*1 = high-school grade point average23 = SAT mathemathics scorey = final college grade point averageRound test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations.a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVAdfMScance FRegression1.76209ResidualTotal91.88CoefficientsStandard Errort Statp-valueIntercept-1.40530.4848X10.0234670.0086666X20.004860.001077

Answered: The admissions officer for Clearwater…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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please assist

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 = -1.41 + 0.0235a1 + 0.00486x2
where
*1 = high-school grade point average
23 = SAT mathemathics score
y = final college grade point average
Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations.
a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
df
MS
cance F
Regression
1.76209
Residual
Total
9
1.88
Coefficients
Standard Error
t Stat
p-value
Intercept
-1.4053
0.4848
X1
0.023467
0.0086666
X2
0.00486
0.001077

Expert Solution

Step 1

To complete the missing entries in this Excel Regression tool output.

$d f (R e g r e s s i o n) = n u m b e r o f i n d e p e n d e n t v a r i a b l e s = 2$

$\begin{array}{rcl} d f (r e s i d u a l) & = & d f (T o t a l) - d f (R e g r e s s i o n) \\ = & 9 - 2 \\ = & 7 \end{array}$

$\begin{array}{rcl} S S E & = & S S T - S S R \\ = & 1.88 - 1.76209 \\ = & 0.11791 \end{array}$

$\begin{array}{rcl} M S R & = & \frac{S S R}{d f (R e g r e s s i o n)} \\ = & \frac{1.76209}{2} \\ = & 0.881045 \end{array}$

$\begin{array}{rcl} M S E & = & \frac{S S E}{d f (r e s i d u a l)} \\ = & \frac{0.1179}{7} \\ = & 0.01684285714 \\ \approx & 0.0168 \end{array}$

F-statistic is given by the formula:

$\begin{array}{rcl} F & = & \frac{M S R}{M S E} \\ = & \frac{0.881045}{0.01684285714} \\ = & 52.30971163 \\ \approx & 52.3100 \end{array}$

Using Excel function "F.DIST.RT(52.31,2,7)", p-value obtained is 0.0001

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