Business Creditcard

8/11/2019 Business Creditcard

1/18

REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT overall_feedback

/METHOD=ENTER customer_service range_products convenience internet_banking mobile

Regression

CT-2014 10:09:34

Active Dataset DataSet0

Filter

Weight

Split File

N of Rows in

Working Data

25

Definition of

Missing

User-defined

missing values

are treated as

Cases Used Statistics are

based on cases

with no missing

values for any

variable used.REGRESSION

/MISSINGLISTWISE

/STATISTICS

COEFF OUTS R

ANOVA

/CRITERIA=PIN(.

05) POUT(.10)

/NOORIGIN

/DEPENDENT

overall_feedback

/METHOD=ENTE

R

customer_service range_products

convenience

internet_banking

mobile bankinProcessor Time 00:00:00.02

Elapsed Time 00:00:00.08

Memory 3700 bytes

Notes

Output Created

Comments

Input

Missing Value

Handling

Syntax

Resources


2/18

Additional

Memory

Required for

Residual Plots

0 bytes

[DataSet0]

Variables

Entered

Variables

Removed Method

1 query_handling,

customer_servi

ce,

internet_bankin

g,

mobile_banking

,

range_products

,phone_banking

, convenienceb

Enter

R R Square

Adjusted R

Square

Std. Error of

the Estimate1 .919

a .844 .776 .549

Sum of Squares df Mean Square F Sig.

Regression 26.139 7 3.734 12.398 .000b

Residual 4.819 16 .301

Total 30.958 23

Variables Entered/Removeda

Model

a. Dependent Variable: overall_feedback

b. All requested variables entered.

Model Summary

Model

a. Predictors: (Constant), query_handling, customer_service, internet_banking,

mobile_banking, range_products, phone_banking, convenience

ANOVAa

Model

1


b. Predictors: (Constant), query_handling, customer_service, internet_banking, mobile_banking,

range_products, phone_banking, convenience

Coefficientsa


3/18

Standardized

Coefficients

B Std. Error Beta

(Constant) -.504 1.315 -.383 .707

customer_servi .366 .145 .315 2.523 .023

range_products .049 .175 .040 .281 .782convenience .672 .158 .714 4.244 .001

internet_bankin -.081 .167 -.074 -.483 .636

mobile_banking .030 .118 .033 .254 .803

phone_banking -.165 .162 -.158 -1.016 .325

query_handling .198 .075 .314 2.649 .018

REGRESSION

/MISSING LISTWISE


/CRITERIA=PIN(.05) POUT(.10) /NOORIGIN



Regression

CT-2014 10:11:47

Active Dataset DataSet0Filter

Weight

Split File

N of Rows in

Working Data

51

Definition of

Missing

User-defined

missing values

are treated as


based on cases

with no missing

values for anyvariable used.

Model

Unstandardized Coefficients

t Sig.

1


Notes

Output Created

Comments

Input

Missing Value

Handling


4/18

REGRESSION

/MISSING

LISTWISE

/STATISTICS

COEFF OUTS R

ANOVA

/CRITERIA=PIN(.

05) POUT(.10)

/NOORIGIN

/DEPENDENT

overall_feedback

/METHOD=ENTE

R

customer_servic

e range_products

convenience

internet_banking

mobile bankinProcessor Time 00:00:00.08


Memory 3700 bytes

Additional

Memory

Required for

Residual Plots

0 bytes

[DataSet0]

VariablesEntered

VariablesRemoved Method

1 query_handling,

internet_bankin

g,

customer_servi

ce,

range_products

, convenience,

phone_banking

,

mobile_bankingb

Enter

Syntax

Resources


Model



Model Summary


5/18

R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .828a .685 .634 .683


Regression 43.650 7 6.236 13.383 .000b

Residual 20.036 43 .466

Total 63.686 50

Standardized

Coefficients

B Std. Error Beta

(Constant) 2.084 .945 2.205 .033

customer_servi -.002 .093 -.003 -.022 .983

range_products .244 .089 .287 2.742 .009

convenience .118 .077 .176 1.541 .131

internet_bankin .233 .110 .216 2.109 .041

mobile_banking -.031 .097 -.042 -.321 .749

phone_banking -.029 .103 -.035 -.282 .779

query_handling .239 .068 .448 3.501 .001

REGRESSION

/MISSING LISTWISE



/NOORIGIN



Regression

CT-2014 10:12:53

Model

a. Predictors: (Constant), query_handling, internet_banking, customer_service,

range_products, convenience, phone_banking, mobile_banking

ANOVAa

Model

1


b. Predictors: (Constant), query_handling, internet_banking, customer_service, range_products, convenience,

phone_banking, mobile_banking

Coefficientsa

Model


t Sig.

1


Notes

Output Created

Comments


6/18


Filter

Weight

Split File

N of Rows in

Working Data

51

Definition of

Missing

User-defined

missing values

are treated as


based on cases

with no missing

values for any

variable used.REGRESSION

/MISSING

LISTWISE

/STATISTICS

COEFF OUTS R

ANOVA

/CRITERIA=PIN(.

05) POUT(.10)

/NOORIGIN

/DEPENDENT

overall_feedback

/METHOD=ENTE

R

customer_servic

e range_products

convenience

internet_bankingmobile bankin

Processor Time 00:00:00.08


Memory 3700 bytes

Additional

Memory

Required for

Residual Plots

0 bytes

[DataSet0]

Variables

Entered

Variables

Removed Method

Input

Missing Value

Handling

Syntax

Resources


Model


7/18

1 query_handling,

mobile_banking

,

customer_servi

ce,

internet_bankin

g,

range_products

,

phone_banking

, convenienceb

Enter

R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .879a .772 .735 .645


Regression 60.620 7 8.660 20.816 .000b

Residual 17.889 43 .416

Total 78.510 50

Standardized

Coefficients

B Std. Error Beta

(Constant) .259 .995 .261 .796customer_servi .082 .099 .075 .828 .412

range_products .197 .107 .186 1.841 .073

convenience .415 .101 .472 4.121 .000

internet_bankin .113 .122 .094 .926 .360

mobile_banking .062 .095 .053 .652 .518

phone_banking -.065 .109 -.058 -.595 .555

query_handling .193 .060 .306 3.213 .002



Model Summary

Model

a. Predictors: (Constant), query_handling, mobile_banking, customer_service,

internet_banking, range_products, phone_banking, convenience

ANOVAa

Model

1


b. Predictors: (Constant), query_handling, mobile_banking, customer_service, internet_banking,

range_products, phone_banking, convenience

Coefficientsa

Model


t Sig.

1


8/18

REGRESSION

/MISSING LISTWISE



/NOORIGIN

/DEPENDENT Overall_Feedback

/METHOD=ENTER Value_Offered Reward_Programs Redemption_Convenience Promotions_Off

Regression

CT-2014 10:22:46


Filter

Weight

Split File

N of Rows in

Working Data

23

Definition of

Missing

User-defined

missing values

are treated as


based on cases

with no missing

values for anyvariable used.REGRESSION

/MISSING

LISTWISE

/STATISTICS

COEFF OUTS R

ANOVA

/CRITERIA=PIN(.

05) POUT(.10)

/NOORIGIN

/DEPENDENT

Overall_Feedbac

k

/METHOD=ENTE

R Value_Offered

Processor Time 00:00:00.11


Memory 2468 bytes


Notes

Output Created

Comments

Input

Missing Value

Handling

Syntax

Resources


9/18

Additional

Memory

Required for

Residual Plots

0 bytes

[DataSet0]

Variables

Entered

Variables

Removed Method

1 Promotions_Off

ers,

Reward_Progra

ms,

Value_Offered,

Redemption_C

onvenienceb

Enter

R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .784a .615 .529 .845


Regression 20.466 4 5.116 7.174 .001b

Residual 12.838 18 .713

Total 33.304 22

Standardized

Coefficients

B Std. Error Beta

(Constant) 1.188 1.827 .650 .524

Value_Offered -.186 .248 -.141 -.749 .463


Model

a. Dependent Variable: Overall_Feedback


Model Summary

Model

a. Predictors: (Constant), Promotions_Offers, Reward_Programs, Value_Offered,

Redemption_Convenience

ANOVAa

Model

1

1


b. Predictors: (Constant), Promotions_Offers, Reward_Programs, Value_Offered, Redemption_Convenience

Coefficientsa

Model


t Sig.


10/18

Reward_Progra .067 .177 .066 .380 .709

Redemption_C

onvenience

.260 .247 .211 1.054 .306

Promotions_Off .722 .239 .670 3.027 .007



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Business Creditcard