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Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .179 .032 .026 2.023 a. Predictors: (Constant), AGE Model Sum of Squares df Mean Square F Sig. 1 Regression 23.784 1 23.784 5.812 .0175 Residual 720.238 176 4.092 Total 744.022 177 a. Dependent Variable: INCOME b. Predictors: (Constant), AGE Coefficients Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 6.784 .911 7.445 .000 AGE -.032 .013 -.179 -2.411 .017 a. Dependent Variable: INCOME What is the slope of the regression equation? 6.784

Name: model summary model r r square adjusted r square std error of the estimate 1 179 032 026 2023 a predictors constant age model sum of squares df mean square f sig 1 regression 23784 1 23784 5 16286
Uploaded: 2022-06-10T23:01:45-08:00
Duration: 1 min 52 s
Channel: T. L.
Description: model summary model r r square adjusted r square std error of the estimate 1 179 032 026 2023 a predictors constant age model sum of squares df mean square f sig 1 regression 23784 1 23784 5 16286

          Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.179	.032	.026	2.023
a. Predictors: (Constant), AGE
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	23.784	1	23.784	5.812	.0175
	Residual	720.238	176	4.092
	Total	744.022	177
a. Dependent Variable: INCOME
b. Predictors: (Constant), AGE
Coefficients
Unstandardized Coefficients	Standardized Coefficients
Model	B	Std. Error	Beta	t	Sig.
1	(Constant)	6.784	.911	7.445	.000
	AGE	-.032	.013	-.179	-2.411	.017
a. Dependent Variable: INCOME
What is the slope of the regression equation?
6.784

model summary model r r square adjusted r square std error of the estimate 1 179 032 026 2023 a predictors constant age model sum of squares df mean square f sig 1 regression 23784 1 23784 5 16286

Added by -Ngeles R.

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