Regression Statistics Multiple R 0.95 R Square 0.90 Adjusted R Square 0.89 Coefficients Intercept 16,600 X Variable 1 74 The cost formula would be a$16,600 + ($74 x 0.95) b.$16, 600 x 0.95 c.$16,600 + $74X d.none of these

Regression Statistics Multiple R 0.95 R Square 0.90 Adjusted R Square 0.89 Coefficients Intercept 16,600 X Variable 1 74 The cost formula would be a$16,600 + ($74 x 0.95) b.$16, 600 x 0.95 c.$16,600 + $74X d.none of these

College Algebra

10th Edition

ISBN:9781337282291

Author:Ron Larson

Publisher:Ron Larson

Chapter3: Polynomial Functions

Section: Chapter Questions

Problem 18T

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Question

Here are some statistics from a regression analysis of the relationship between overhead costs and machine hours.

Regression Statistics
Multiple R	0.95
R Square	0.90
Adjusted R Square	0.89
Coefficients
Intercept	16,600
X Variable 1	74

The cost formula would be

a$16,600 + ($74 x 0.95)

b.$16, 600 x 0.95

c.$16,600 + $74X

d.none of these

Definition Definition Statistical method that estimates the relationship between a dependent variable and one or more independent variables. In regression analysis, dependent variables are called outcome variables and independent variables are called predictors.

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