Considering we want to develop a predictive model to predict the variable "credibility" answer the following question1) If we want to develop a logistic regression model how many coefficients, we will have in the logistic regression equation excluding intercept. Please answer in sentense Creditability Credit Amount Length of current employment Sex & Marital Status Age (years)11049222127991136841232122392171382241483398391361401098653758233905366187241957317582311936232647443939402121211222222211LLELAME1131131113WW11311AWNAWNNW WWWW NA233333223423413M Table 1. Credibility data detailsVariableMeaningCredibilityCreditamountLength ofemploymentSex andMaritalStatusAge1= good2= badNo description needed1= less than 20 years2= between 20 and 40 years3= between 40 and 60 years1= married made2= married female3= divorced male or femaleAge in years

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Considering we want to develop a predictive model to predict the variable "credibility" answer the following question 1) If we want to develop a logistic regression model how many coefficients, we will have in the logistic regression equation excluding intercept. Please answer in sentense

Considering we want to develop a predictive model to predict the variable "credibility" answer the following question 1) If we want to develop a logistic regression model how many coefficients, we will have in the logistic regression equation excluding intercept. Please answer in sentense

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Considering we want to develop a predictive model to predict the variable "credibility" answer the following question

1) If we want to develop a logistic regression model how many coefficients, we will have in the logistic regression equation excluding intercept. Please answer in sentense

Creditability Credit Amount Length of current employment Sex & Marital Status Age (years)
1
1049
2
2
21
2799
1
1
36
841
23
2122
39
2171
38
2241
48
3398
39
1361
40
1098
65
3758
23
3905
36
6187
24
1957
31
7582
31
1936
23
2647
44
3939
40
2
1
2
1
2
1
1
2
2
2
2
2
2
2
1
1
LLELAME
1
1
3
1
1
3
1
1
1
3
WW
1
1
3
1
1
AWNAWNNW WWWW NA
2
3
3
3
3
3
2
2
3
4
2
3
4
1
3
M

Table 1. Credibility data details
Variable
Meaning
Credibility
Credit
amount
Length of
employment
Sex and
Marital
Status
Age
1= good
2= bad
No description needed
1= less than 20 years
2= between 20 and 40 years
3= between 40 and 60 years
1= married made
2= married female
3= divorced male or female
Age in years

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