6. Parker, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R 0.8274 R Square 0.8229 Observations 26 Coefficients Standard Error T Stat Intercept 23,859 5,196 3.65 Production (X) 3.13 0.2765 11.19 What total cost would Parker predict for a month in which they sold 3,500 units

Respuesta :

Answer:

"34,814" is the correct solution.

Step-by-step explanation:

The given values are:

Intercept coefficient,

[tex]\beta_0 = 23,859[/tex]

Production coefficient,

[tex]\beta_1 = 3.13[/tex]

Units sold,

x = 3,500

Now,

The total cost will be:

⇒  [tex]\bar{y}=\beta_0+\beta_1 x[/tex]

On substituting the estimated values, we get

⇒     [tex]=23,859+3.13\times 3,500[/tex]

⇒     [tex]=23,859+10,955[/tex]

⇒     [tex]=34,814[/tex]