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This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 x (X1 x 2.32) + (X2 x -1.3)
Y = 12.567 + (X1 + 2.32) + (X2 + -1.3)

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise

This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 + (X1 x 2.32) + (X2 x -1.3)
Y = 12.567 + (X1 + 2.32) + (X2 + -1.3)

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise

This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 x ((X1 x 2.32) + (X2 x -1.3))
Y = 12.567 + ((X1 + 2.32) + (X2 + -1.3))

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise

This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 x (X1 x 2.32) + (X2 x -1.3)
Y = 12.567 + (X1 + 2.32) + (X2 + -1.3)

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise

This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 x ((X1 + 2.32) + (X2 + -1.3))
Y = 12.567 + ((X1 + 2.32) + (X2 + -1.3))

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise

This is from an assignment I need to finish but I need some advice on where/what to investigate further please (absolutely new to stats):

You use regression to generate a function that operates on two variables (X1 and X2) to predict a label (Y).

The regression output shows the following coefficients:

Intercept: 12.576
X1: 2.32
X2: -1.3

Which formulae describes the regression function?

Y = 12.567 + 2.32 + -1.3
Y = 12.567 x ((X1 x 2.32) + (X2 x -1.3))
Y = 12.567 + ((X1 + 2.32) + (X2 + -1.3))

My thinking :

sample regression line is: ŷ = b0 + b1x.

thus : y = 12.576 + (regression coefficient)

and regression coefficient = y = mx + b

I am out of my depth - please advise