The following Computer output presents the least-squares regression line for predicting the price of a certain commodity from the price of a barrel of oil.

_

Predictor

Coef

SE Coef

T

P

Constant

147.851724

68.827814

2.148139

0.098187

Oil

0.493103

0.691769

0.712815

0.515337

_

Write the equation of the least-squares regression line.

y = 0.098187 + 0.515337x
y = 2.148139 + 0.712815x
y = 147.851724 + 0.493103x
y =0.493103 + 147.851724x

Computer output presents the least-squares for predicting the price of a certain commodity from the price of a barrel of oil is y=2.148139 +0.712815x

A regression is a statistical approach that relates a based variable to one or extra impartial (explanatory) variables. A regression version is able to expose whether modifications discovered in the structured variable are related to modifications in one or more of the explanatory variables.

A regression analysis is completed for considered one of purposes: so that it will expect the price of the established variable for individuals for whom some statistics concerning the explanatory variables is to be had, or if you want to estimate the effect of some explanatory variable at the structured variable.

COMMODITY = - 43.987621 + 23.368407 OIL

OIL PRICE = $ 114 /per barrel

Commodity = - 43.987621 + 23.3658407*(144)

Commodity = $2620.010777

according to the options B is the answer.

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