Question

A computer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three independent variables. The three independent variables are price per unit (Price in $100s), advertising (ADV in $1,000s) and the number of product lines (Lines). Part of the regression results is shown below.

		Coefficient	Standard Error
Intercept		1.0211	22.8752
Price		-0.1524	0.1411
ADV		0.8849	0.2886
Lines		-0.1463	1.5340
Analysis of Variance
Source of Variation		Degrees of Freedom	Sum of Squares
Regression			2708.61
Error (Residuals) Required:		14	2840.51
a.	Use the above results and write the regression equation that can be used to predict sales.
b.	If the manufacturer has 10 product lines, advertising of $40,000, and the price per unit is $3,000, what is your estimate of their sales?
c.	Compute the coefficient of determination and fully interpret its meaning.
d.	At a = 0.05, test to see if there is a significant relationship between sales and unit price.
e.	At a = 0.05, test to see if there is a significant relationship between sales and the number of product lines.
f.	Is the regression model significant?
g.	Fully interpret the meaning of the regression (coefficient of price) per unit that is, the slope for the price per unit.

Answer 1

The value of n is obtaind from ANOVA table:

Erro df= n-k-1=14

here k=3 (no. of independent variables)

hence, n=18