The following regression is fitted using variables identified that could be related to student requested loan amount, LOAN-AMT($) for returning students of a certain University. LOAN - AMT = a + ß ACCEPT + y PREV + A OUTS Where ACCEPT = the percentage of applicants that was accepted by the university, PREV= previous loan amount and OUTS -outstanding loan amount The data was processed using MNITAB and the following is an extract of the output obtained:

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ISBN:9781119256830
Author:Amos Gilat
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The following regression is fitted using variables identified that could be related to student
requested
loan amount, LOAN-AMT($) for returning students of a certain University.
LOAN AMT = a + ß ACCEPT + y PREV + λ OUTS
Where ACCEPT = the percentage of applicants that was accepted by the university, PREV=
previous loan amount and OUTS outstanding loan amount
The data was processed using MNITAB and the following is an extract of the output obtained:
Predictor
Constant
ACCEPT
PREV
OUTS
S = 2685
Coef
-26780
116.00
-4.21
70.85
R-Sq = 69.6%
Analysis of Variance
DF
3
Source
Regression
Residual Error 49
Total
52
SS
EXHIBIT 2
St Dev
6115
37.17
14.12
15.77
808139371
353193051
1161332421
a) What is dependent and independent variables?
b) Fully write out the regression equation
T
*
3.14
-0.30
4.49
MS
269379790
7208021
c) What is the sample size used in this investigation?
d) Fill in the blanks identified by *** and ****.
e) Is ẞ significant, at the 5% level of significance?
P
0.000
0.003
**
0.000
R-Sq (adj)
= 67.7%
F
37.37
P
0.00
Transcribed Image Text:The following regression is fitted using variables identified that could be related to student requested loan amount, LOAN-AMT($) for returning students of a certain University. LOAN AMT = a + ß ACCEPT + y PREV + λ OUTS Where ACCEPT = the percentage of applicants that was accepted by the university, PREV= previous loan amount and OUTS outstanding loan amount The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Constant ACCEPT PREV OUTS S = 2685 Coef -26780 116.00 -4.21 70.85 R-Sq = 69.6% Analysis of Variance DF 3 Source Regression Residual Error 49 Total 52 SS EXHIBIT 2 St Dev 6115 37.17 14.12 15.77 808139371 353193051 1161332421 a) What is dependent and independent variables? b) Fully write out the regression equation T * 3.14 -0.30 4.49 MS 269379790 7208021 c) What is the sample size used in this investigation? d) Fill in the blanks identified by *** and ****. e) Is ẞ significant, at the 5% level of significance? P 0.000 0.003 ** 0.000 R-Sq (adj) = 67.7% F 37.37 P 0.00
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