A company conducted a study to determine the amount charged on credit cards The independent variables used were household size and income (in thousands) Fifty households were studied and the results of the multiple regression analysis are given Regression Variables Entered Removed a Model Variables Entered Variables Removed Method 1 HouseholdSize Stepwise (Criteria Probability of F to enter 100) 2 Income Stepwise (Criteria Probability of F to enter 100) a Dependent Variable AmtCharged Model Summary Model R R Square Adjusted R Square Std Error of the Estimate 1 753 a 567 558 620 793 2 909 b 826 818 398 091 a Predictors (Constant), HouseholdSize b Predictors (Constant), HouseholdSize, Income ANOVA a Model Sum of Squares df Mean Square F Sig 1 Regression 24200717 481 1 24200717 481 62 796 000 b Residual 18498431 339 48 385383 986 Total 42699148 820 49 2 Regression 35250755 672 2 17625377 836 111 218 000 c Residual 7448393 148 47 158476 450 Total 42699148 820 49 a Dependent Variable AmtCharged b Predictors (Constant), HouseholdSize c Predictors (Constant), HouseholdSize, Income Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig B Std Error Beta 1 (Constant) 2581 941 195 263 13 223 000 HouseholdSize 404 128 50 998 753 7 924 000 2 (Constant) 1304 905 197 655 6 602 000 HouseholdSize 356 296 33 201 664 10 732 000 Income 33 133 3 968 516 8 350 000 a Dependent Variable AmtCharged Excluded Variables a Model Beta In t Sig Partial Correlation Collinearity Statistics Tolerance 1 Income 516 b 8 350 000 773 970 a Dependent Variable AmtCharged b Predictors in the Model (Constant), HouseholdSize What is the regression equation

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A company conducted a study to determine the amount charged on credit cards. The independent variables used were household size and income (in thousands). Fifty

A company conducted a study to determine the amount charged on credit cards. The independent variables used were household size and income (in thousands). Fifty households were studied and the results of the multiple regression analysis are given.

Regression

Variables Entered/Removed^a
Model	Variables Entered	Variables Removed	Method
1	HouseholdSize	.	Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
2	Income	.	Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
a. Dependent Variable: AmtCharged

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.753^a	.567	.558	620.793
2	.909^b	.826	.818	398.091
a. Predictors: (Constant), HouseholdSize
b. Predictors: (Constant), HouseholdSize, Income

ANOVA^a
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	24200717.481	1	24200717.481	62.796	.000^b
Residual	18498431.339	48	385383.986
Total	42699148.820	49
2	Regression	35250755.672	2	17625377.836	111.218	.000^c
Residual	7448393.148	47	158476.450
Total	42699148.820	49
a. Dependent Variable: AmtCharged
b. Predictors: (Constant), HouseholdSize
c. Predictors: (Constant), HouseholdSize, Income

Coefficients^a
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	2581.941	195.263		13.223	.000
HouseholdSize	404.128	50.998	.753	7.924	.000
2	(Constant)	1304.905	197.655		6.602	.000
HouseholdSize	356.296	33.201	.664	10.732	.000
Income	33.133	3.968	.516	8.350	.000
a. Dependent Variable: AmtCharged

Excluded Variables^a
Model	Beta In	t	Sig.	Partial Correlation	Collinearity Statistics
Tolerance
1	Income	.516^b	8.350	.000	.773	.970
a. Dependent Variable: AmtCharged
b. Predictors in the Model: (Constant), HouseholdSize