Answer:
Correct option: (b) 185.4.
Step-by-step explanation:
The regression analysis is used to predict the value of the response variable (<em>Y</em>) based on one or more than one experimental variable(s) (<em>X</em>).
The general form of the regression equation is:

Here,
<em>α</em> = intercept
= slope coefficient, (i = 1, 2, 3, ...n)
The regression equation of costs of a product (<em>y</em>) based on the time to make the product (<em>x</em>₁), the number of different materials used (<em>x</em>₂), and the amount spent on marketing the product (<em>x</em>₃) is:

The information provided is:
<em>x</em>₁ = 5 hours
<em>x</em>₂ = 4
<em>x</em>₃ = $100
Compute the value of <em>y</em> for the given values as follows:


Thus, the estimated cost of a product is $185.4.