26 A microcomputer 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) 14 2840 51 26 Compute the coefficient of determination and fully interpret its meaning Question 26 options A) 0 188 18 8 of the variation in sales is explained by variations in the three independent variables B) 0 312 31 2 of the variation in sales is explained by variations in the three independent variables C) 0 488 48 8 of the variation in sales is explained by variations in the three independent variables D) Non of these alternatives is correct 27 A microcomputer 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) 14 2840 51 27 At 0 05,conduct t test to see if there is a significant relationship between sales and the number of product lines p value is between 2 and 4 What is your conclusion Question 27 options A) t 0 027 p value is between 2 and 4 do not reject H 0 not significant at 0 05 B) t 0 031 p value is between 2 and 4 do not reject H 0 not significant at 0 05 C) t 0 095 p value is between 2 and 4 do not reject H 0 not significant at 0 05 D) Non of these alternatives is correct 28 A microcomputer 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) 14 2840 51 28 At 0 05, conduct t test to see if there is a significant relationship between sales and unit price If p value between 2 and 4 what is your conclusion Question 28 options A) t 1 08 p value is between 2 and 4 do not reject H 0 not significant at 0 05 B) t 3 28 p value is between 2 and 4 do not reject H 0 not significant at 0 05 C) t 2 68 p value is between 2 and 4 reject H 0 its significant at 0 05 D) t 1 56 p value is between 2 and 4 reject H 0 its significant at 0 05 29 A microcomputer 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) 14 2840 51 29 Is the regression model significant (Perform an F test ) What is your conclusion if p value is between 01 and 025 Question 29 options A) F 3 45 p value is between 01 and 025 reject H 0 model is not significant at 0 05 B) F 2 15 p value is between 01 and 025 reject H 0 model is significant C) F 4 45 p value is between 01 and 025 reject H 0 model is significant at 0 05 D) Non of these alternatives is correct 30 A microcomputer 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) 14 2840 51 30 Fully interpret (coefficient of price) per unit that is, the slope for the price per unit Question 30 options A) As the price is increased by $100, sales are expected to increase by $1,524 50 B) As the price is increased by $1, sales are expected to decrease by $1,524 50 C) As the price is increased by $200, sales are expected to increase by $1,524 50 D) As the price is increased by $100, sales are expected to decrease by $1,524 50

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Question: 26. A microcomputer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three independent variables. The three independent variables are price

26.

A microcomputer 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)	14	2840.51

26. Compute the coefficient of determination and fully interpret its meaning

Question 26 options:

A)	0.188; 18.8% of the variation in sales is explained by variations in the three independent variables

B)	0.312; 31.2% of the variation in sales is explained by variations in the three independent variables

C)	0.488; 48.8% of the variation in sales is explained by variations in the three independent variables

D)	Non of these alternatives is correct

27.

	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)	14	2840.51

27. At = 0.05,conduct t- test to see if there is a significant relationship between sales and the number of product lines. ; p-value is between .2 and .4. What is your conclusion?

Question 27 options:

A)	t = -0.027; p-value is between .2 and .4; do not reject H₀; not significant at = 0.05

B)	t = 0.031; p-value is between .2 and .4; do not reject H₀; not significant at = 0.05

C)	t = -0.095; p-value is between .2 and .4; do not reject H₀; not significant at = 0.05

D)	Non of these alternatives is correct

28.

	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)	14	2840.51

28. At = 0.05, conduct t-test to see if there is a significant relationship between sales and unit price. If p-value between .2 and .4 what is your conclusion?

Question 28 options:

A)	t = -1.08; p-value is between .2 and .4; do not reject H₀; not significant at = 0.05

B)	t = -3.28; p-value is between .2 and .4; do not reject H₀; not significant at = 0.05

C)	t = 2.68; p-value is between .2 and .4; reject H₀; its significant at = 0.05

D)	t = -1.56; p-value is between .2 and .4; reject H₀; its significant at = 0.05

29.

	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)	14	2840.51

29. Is the regression model significant? (Perform an F test.) What is your conclusion if p-value is between .01 and .025?

Question 29 options:

A)	F = 3.45; p-value is between .01 and .025; reject H₀; model is not significant at = 0.05

B)	F = 2.15; p-value is between .01 and .025; reject H₀; model is significant

C)	F = 4.45; p-value is between .01 and .025; reject H₀; model is significant at = 0.05

D)	Non of these alternatives is correct

30.

	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)	14	2840.51

30. Fully interpret (coefficient of price) per unit that is, the slope for the price per unit

Question 30 options:

A)	As the price is increased by $100, sales are expected to increase by $1,524.50

B)	As the price is increased by $1, sales are expected to decrease by $1,524.50

C)	As the price is increased by $200, sales are expected to increase by $1,524.50

D)	As the price is increased by $100, sales are expected to decrease by $1,524.50

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