39 49 57 71 81 86 y 3 6 12 22 28 41 Utilizing Linear Regression Analysis (Least-Squares Line), create a linear equation that best fits the above paired data set of two variables. Use the following format for the equation: y = a + bx. Group of answer choices A. y = -29.5 + 0.755x B. y = 18.7 + 0.638x C. y = -18.7 + 0.638x D. y = 0.295x - 75.5

39 49 57 71 81 86 y 3 6 12 22 28 41 Utilizing Linear Regression Analysis (Least-Squares Line), create a linear equation that best fits the above paired data set of two variables. Use the following format for the equation: y = a + bx. Group of answer choices A. y = -29.5 + 0.755x B. y = 18.7 + 0.638x C. y = -18.7 + 0.638x D. y = 0.295x - 75.5

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter2: Matrices

Section2.6: More Applications Of Matrix Operations

Problem 18E

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Question

x	39	49	57	71	81	86
y	3	6	12	22	28	41

Utilizing Linear Regression Analysis (Least-Squares Line), create a linear equation that best fits the above paired data set of two variables. Use the following format for the equation: y = a + bx.

Group of answer choices

A. y = -29.5 + 0.755x

B. y = 18.7 + 0.638x

C. y = -18.7 + 0.638x

D. y = 0.295x - 75.5

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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