y = demand for the large bottle of Fresh in the sales period(Demand) x1 = the price of product 1 x2 = the price of product 2 x3 = the advertising expenditure for Fresh x4 = the price difference in the sales period Adver = types of advertising campaigns Campaign A consists entirely of television commercials, campaign B consists of a balanced mixture of television and radio commercials, and campaign C consists of a balanced mixture of television, radio, newspaper, an dmagazine ads. To ultimately increase the demand for Fresh, Enterprise Industries’ marketing department is comparing the effectiveness of three different advertising campaigns. To compare the effectiveness of advertising campaigns A, B, and C, we define two dummy variables. Specifically, DB is 1 if campaign B is used and 0 otherwise, DC is 1 if campaign C is used and 0 otherwise. Our proposed model is y = β0 + β1x4 + β2x3 + β3x 2 3 + β4x4x3 + β5DB + β6DC
y = demand for the large bottle of Fresh in the sales period(Demand)
x1 = the price of product 1
x2 = the price of product 2
x3 = the advertising expenditure for Fresh
x4 = the price difference in the sales period
Adver = types of advertising campaigns
Campaign A consists entirely of television commercials, campaign B consists of a balanced
mixture of television and radio commercials, and campaign C consists of a balanced mixture of
television, radio, newspaper, an dmagazine ads. To ultimately increase the demand for Fresh,
Enterprise Industries’ marketing department is comparing the effectiveness of three different
advertising campaigns. To compare the effectiveness of advertising campaigns A, B, and C, we
define two dummy variables. Specifically, DB is 1 if campaign B is used and 0 otherwise, DC is
1 if campaign C is used and 0 otherwise. Our proposed model is
y = β0 + β1x4 + β2x3 + β3x 2 3 + β4x4x3 + β5DB + β6DC
![0
1
2
3
4
5
6
7
8
9
О
1
2
3
4
5
6
7
8
9
0
1
2
A
3.80
3.85
3.90
3.90
3.70
3.75
3.75
3.80
3.70
3.80
3.70
3.80
3.80
3.75
3.70
3.55
3.60
3.65
3.70
3.75
3.80
3.70
B
3.65
4.00
4.10
4.00
4.10
4.20
4.10
4.10
4.20
4.30
4.10
3.75
3.75
3.65
3.90
3.65
4.10
4.25
3.65
3.75
3.85
4.25
5.25
6.00
6.50
6.25
7.00
6.90
6.80
6.80
7.10
7.00
6.80
6.50
6.25
6.00
6.50
7.00
6.80
6.80
6.50
5.75
5.80
6.80
-0.15
0.15
0.20
0.10
0.40
0.45
0.35
0.30
0.50
0.50
0.40
-0.05
-0.05
-0.10
0.20
0.10
0.50
0.60
-0.05
0.00
0.05
0.55
E
7.10 B
8.00 С
7.89 A
8.15 C
9.10 C
8.86 A
8.90 B
8.87 B
9.26 B
9.00 A
8.75 B
7.95 B
7.65 C
7.27 A
8.00 A
8.50 A
8.75 A
9.21 B
8.27 с
7.67 B
7.93 C
9.26 C
F
0
0
1
0
0
1
0
0
0
1
0
0
0
1
1
1
1
0
0
0
0
0
H
1
гоо 0 0 0
0
0
1
1
1
0
1
1
0 0 0 ОО-ого
0
0
1
0
1
0
0
огогто
1
1
1
0
0
0
0
0
0
ог о 0 0 0 0гогг
1
0
1
1](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe168234c-8641-43ba-b22b-28f74f97e6ae%2Fd66cc7cd-5151-4631-ad54-bf0bea2da8ed%2F7zsaahj_processed.png&w=3840&q=75)
![(a) Estimate ß; for each i =
(b) Set a = 0.05 and test
i = 0, 1, 2, 3, 4.
Ho : Bi = 0,
Ha : Bi #0
for each i = 1, 2, 3, 4. What do you conclude? Interpret your result based on your hypothesis
test on each i. (Stating that we reject(do not reject) Ho or significant (not significant) is
not enough. Need to explain the relationship between factors and the consequences.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe168234c-8641-43ba-b22b-28f74f97e6ae%2Fd66cc7cd-5151-4631-ad54-bf0bea2da8ed%2Fyisgl2l_processed.png&w=3840&q=75)
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