Variables in the Equation S.E. Wald Step 0 Constant -.765 .107 50.764 1 .000 .465 X (1) Exp(B) = .465, and is equal to both e and the fraction - y values z = X = and y = B df Sig. Exp (B) The numeric
Variables in the Equation S.E. Wald Step 0 Constant -.765 .107 50.764 1 .000 .465 X (1) Exp(B) = .465, and is equal to both e and the fraction - y values z = X = and y = B df Sig. Exp (B) The numeric
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:(G) This is a method of changing all the values of a variable by using some
mathematical operation.
(H)
is the case when two or more independent
variables are highly correlated. Its occurrence can cause difficulties in
multiple regression.
A dataset of 400 prospective students has a binary response outcome variable called
admit, which is equal to 1 if the individual was admitted to graduate school, and 0
otherwise. There are three predictor variables: gre, gpa, and rank. gre and gpa are
continuous quantitative variables. The qualitative variable undergraduate rank takes on
the values 1 through 4. Institutions with a rank of 1 have the highest prestige, while those
with a rank of 4 have the lowest. Schools with a rank of 4 act as the control group.
SPSS gives the following analyses for the logistic regression model:
Classification Tablea,b
Predicted
admit
Percentage
1
Observed
Correct
Step 0
admit
0
273
1
127
0
Overall Percentage
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
B
S.E.
Wald
Step 0
Constant
-.765
.107
50.764
1
.000
.465
X
(I) Exp(B) = .465, and is equal to both e and the fraction
y
values z =
,X =
, and y =
0
0
100.0
.0
68.3
df
Sig.
Exp(B)
The numeric
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