Which attribute is the single poorest predictor of season ticket renewal?

PerformancesAttended

PricePerTicket

ConcessionVouchers

AvgMinutesBeforeCurtain

exceeded the range established by the training data?

$148$

$13$

PricePerTicket

NumberOfTickets

PricePerTicket and NumberOfTickets have the exact same predictive strength in this model.

Neither PricePerTicket nor NumberOfTickets have predictive strength in this model.

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.

LogisticTrainingModel

list $[30]($S$3$: glm$,$ Im$)$

double $[7]$

double $[377]$

double $[377]$

double $[377]$

double $77$

integer $[1]$

list $[5]($S$3$: qr$)$

list $[13]($S$3$: family$)$

double $[377]$

double $[1]$

double $[1]$

double $[1]$

integer $[1]$

double $[377]$

double $[377]$

integer $[1]$

integer $[1]$

double $[377]$

logical $[1]$

logical $[1]$

List of length $30$

$39\mathrm{.}4822-0\mathrm{.}71076\mathrm{.}9192-3\mathrm{.}69520\mathrm{.}55810\mathrm{.}0818$dots

$-2\mathrm{.}72-1\mathrm{.}001\mathrm{.}001\mathrm{.}001\mathrm{.}001\mathrm{.}00$dots

$6\mathrm{.}33e-015\mathrm{.}20e-061\mathrm{.}00e+001\mathrm{.}00e+001\mathrm{.}00e+001\mathrm{.}00e+00$dots

$-0\mathrm{.}1540\mathrm{.}1720\mathrm{.}136-1\mathrm{.}719-0\mathrm{.}937-1\mathrm{.}871$dots

$-2\mathrm{.}13920\mathrm{.}00000\mathrm{.}00000\mathrm{.}00000\mathrm{.}00000\mathrm{.}0000-157\mathrm{.}1020-9\mathrm{.}5080$dots

$7$

List of length $5$

List of length $13$

$0\mathrm{.}544-12\mathrm{.}16818\mathrm{.}41612\mathrm{.}78612\mathrm{.}42823\mathrm{.}099$dots

$29\mathrm{.}0822$

$43\mathrm{.}0822$

$507\mathrm{.}6125$

$11$

$2\mathrm{.}32$e$-015\mathrm{.}20$e$-061\mathrm{.}00$e$-082\mathrm{.}80$e$-064\mathrm{.}00$e$-069\mathrm{.}30$e$-11...$

$111111$dots

$370$

$376$

$001111$dots

TRUE

FALSE

$($No selection$)$

Console Terminal $$ Background Jobs $**$

R $4\mathrm{.}3\mathrm{.}2\frac{}{}$

$>$ summary$($LogisTrainMode$1)$

cal$1$:

glm$($formula $=$ Renewedsubscription $.,$ family $=$ binomial, data $=$ 'Logistic$+$Regression$+$Training'$[,$

$-1])$

Coefficients:

$($Intercept$)$ Estimate std$.$ Error $z$ value $Pr(>|z|)$

PricePerTicket $39\mathrm{.}48217,14\mathrm{.}06179,2\mathrm{.}808,0\mathrm{.}00499$

NumberofTickets $-0\mathrm{.}71073,0\mathrm{.}22775,-3\mathrm{.}121,0\mathrm{.}00180$

Differentusers $-3\mathrm{.}69515,1\mathrm{.}14751,-3\mathrm{.}220,0\mathrm{.}00128$

Concessionvouchers $0\mathrm{.}55813,0\mathrm{.}49390,1\mathrm{.}130,0\mathrm{.}25846$

AvgMinutesBeforecurtain $0\mathrm{.}08180,0\mathrm{.}04101,1\mathrm{.}995,0\mathrm{.}04609*$

PerformancesAttended $1\mathrm{.}61087,0\mathrm{.}76297,2\mathrm{.}111,0\mathrm{.}03475*$

Signif. codes: $0\text{'}$sk$*\text{'}0\mathrm{.}001\text{'}**\text{'}0\mathrm{.}01\text{'}*0\mathrm{.}05\text{'}.0\mathrm{.}1\text{'}\text{'}1$

$($Dispersion parameter for binomial family taken to be $1)$

Nu$11$ deviance: $507\mathrm{.}613$ on $376$ degrees of freedom

Residual deviance: $29\mathrm{.}082$ on $370$ degrees of freedom

AIC : $43\mathrm{.}082$

Number of Fisher scoring iterations: $11$

Number of Fisher scoring iterations: $11$