PerformancesAttended OpricePerTicket O ConcessionVouchers AvgMinutesBeforeCurtain ow many observations had to be removed from the scoring data set because one or more independent variable values exceeded the M ange established by the training data? 148 13 20 01 onsidering all properties of the logistic regression model, which attribute is a better predictor of season ticket renewal? PricePerTicket NumberOffickets PricePerTicket and NumberOffickets have the exact same predictive strength in this model. ONeither PricePerTicket nor NumberOffickets have predictive strength in this model. ased on the coefficients in the logistic regression model, when a larger number of different people use a patron's season tickets to tend performances, what effect does that have on the patron's likelihood of renewing his or her subscription? M Call: gln(formula RenewedSubscription family binomial, data Logistic+Regression Training -1]) Coefficients: - (Intercept) PricePerTicket Number of Tickets Estimate Std. Error z value Pr(>1z) 39.48217 14.06179 2.808 0.00499** -0.71073 0.22775 -3.121 0.00180 6.91922 2.24157 3.087 0.00202 ** Different users -3.69515 1.14751 -3.220 0.00128 ** Concessionvouchers 0.55813 0.49390 1.130 0.25846 Avgvinutesteforecurtain 0.08180 0.04101 1.995 0.04609- PerformancesAttended 1.61087 0.76297 2.111 0.03475- signif. codes: 0*** 0.001 0.01 0.05 0.1'1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 507.613 on 376 degrees of freedom Residual deviance: 29.082 on 370 degrees of freedom AIC: 43.082
PerformancesAttended OpricePerTicket O ConcessionVouchers AvgMinutesBeforeCurtain ow many observations had to be removed from the scoring data set because one or more independent variable values exceeded the M ange established by the training data? 148 13 20 01 onsidering all properties of the logistic regression model, which attribute is a better predictor of season ticket renewal? PricePerTicket NumberOffickets PricePerTicket and NumberOffickets have the exact same predictive strength in this model. ONeither PricePerTicket nor NumberOffickets have predictive strength in this model. ased on the coefficients in the logistic regression model, when a larger number of different people use a patron's season tickets to tend performances, what effect does that have on the patron's likelihood of renewing his or her subscription? M Call: gln(formula RenewedSubscription family binomial, data Logistic+Regression Training -1]) Coefficients: - (Intercept) PricePerTicket Number of Tickets Estimate Std. Error z value Pr(>1z) 39.48217 14.06179 2.808 0.00499** -0.71073 0.22775 -3.121 0.00180 6.91922 2.24157 3.087 0.00202 ** Different users -3.69515 1.14751 -3.220 0.00128 ** Concessionvouchers 0.55813 0.49390 1.130 0.25846 Avgvinutesteforecurtain 0.08180 0.04101 1.995 0.04609- PerformancesAttended 1.61087 0.76297 2.111 0.03475- signif. codes: 0*** 0.001 0.01 0.05 0.1'1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 507.613 on 376 degrees of freedom Residual deviance: 29.082 on 370 degrees of freedom AIC: 43.082
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
![2
3
4
5
Which attribute is the single poorest predictor of season ticket renewal?
PerformancesAttended
O PricePer Ticket
O ConcessionVouchers
Ⓒ AvgMinutesBeforeCurtain
How many observations had to be removed from the scoring data set because one or more independent variable values exceeded the
range established by the training data?
148
13
30
01
Considering all properties of the logistic regression model, which attribute is a better predictor of season ticket renewal?
PricePer Ticket
NumberOfTickets
O PricePer Ticket and NumberOfTickets have the exact same predictive strength in this model.
ONeither PricePerTicket nor NumberOfTickets have predictive strength in this model.
Based on the coefficients in the logistic regression model, when a larger number of different people use a patron's season tickets to
attend performances, what effect does that have on the patron's likelihood of renewing his or her subscription?
0000
The patron is more likely to renew.
The patron is less likely to renew.
The patron is neither more nor less likely to renew.
The patron is more likely to renew, but only if the price per ticket decreases.
On which of the following patrons would the theater want to spend the least amount of marketing money?
2782
6933
1012
5240
M
M
A
M
Call:
-
glm (formula = Renewedsubscription, family binomial, data = 'Logistic+Regression+Training [.
-1])
Coefficients:
-
Estimate Std. Error z value Pr (>1z)
(Intercept)
39.48217 14.06179 2.808 0.00499 **
PricePerTicket
-0.71073 0.22775 -3.121 0.00180 **
Number of Tickets
6.91922
2.24157
3.087 0.00202 **
Different users
-3.69515 1.14751 -3.220 0.00128 **
Concessionvouchers
0.55813 0.49390 1.130 0.25846
AvgMinutesBeforeCurtain 0.08180. 0.04101 1.995 0.04609 *
PerformancesAttended 1.61087 0.76297 2.111 0.03475 *.
signif. codes: 0 ***** 0.001 **** 0.01 0.05. 0.1 1
4 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 507.613 on 376 degrees of freedom
Residual deviance: 29.082 on 370 degrees of freedom
AIC: 43.082
Number of Fisher scoring iterations: 11](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdd9df6ec-2031-4bd9-a4fe-f5a98835f890%2F49762921-3dbe-4117-ab29-45dd4dda6975%2F9bzee8p_processed.jpeg&w=3840&q=75)
Transcribed Image Text:2
3
4
5
Which attribute is the single poorest predictor of season ticket renewal?
PerformancesAttended
O PricePer Ticket
O ConcessionVouchers
Ⓒ AvgMinutesBeforeCurtain
How many observations had to be removed from the scoring data set because one or more independent variable values exceeded the
range established by the training data?
148
13
30
01
Considering all properties of the logistic regression model, which attribute is a better predictor of season ticket renewal?
PricePer Ticket
NumberOfTickets
O PricePer Ticket and NumberOfTickets have the exact same predictive strength in this model.
ONeither PricePerTicket nor NumberOfTickets have predictive strength in this model.
Based on the coefficients in the logistic regression model, when a larger number of different people use a patron's season tickets to
attend performances, what effect does that have on the patron's likelihood of renewing his or her subscription?
0000
The patron is more likely to renew.
The patron is less likely to renew.
The patron is neither more nor less likely to renew.
The patron is more likely to renew, but only if the price per ticket decreases.
On which of the following patrons would the theater want to spend the least amount of marketing money?
2782
6933
1012
5240
M
M
A
M
Call:
-
glm (formula = Renewedsubscription, family binomial, data = 'Logistic+Regression+Training [.
-1])
Coefficients:
-
Estimate Std. Error z value Pr (>1z)
(Intercept)
39.48217 14.06179 2.808 0.00499 **
PricePerTicket
-0.71073 0.22775 -3.121 0.00180 **
Number of Tickets
6.91922
2.24157
3.087 0.00202 **
Different users
-3.69515 1.14751 -3.220 0.00128 **
Concessionvouchers
0.55813 0.49390 1.130 0.25846
AvgMinutesBeforeCurtain 0.08180. 0.04101 1.995 0.04609 *
PerformancesAttended 1.61087 0.76297 2.111 0.03475 *.
signif. codes: 0 ***** 0.001 **** 0.01 0.05. 0.1 1
4 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 507.613 on 376 degrees of freedom
Residual deviance: 29.082 on 370 degrees of freedom
AIC: 43.082
Number of Fisher scoring iterations: 11
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