Annabel, a retail analyst, has been following Under Armour, Incorporated, the pioneer in the compression-gear market. Compression garments are meant to keep moisture away from a wearer's body during athletic activities in warm and cool weather. Annabel believes that the Under Armour brand attracts a younger customer relative to other companies. The accompanying file includes data on the age of the customers and whether or not they purchased Under Armour (Purchase; 1 for purchase. 0 otherwise). Click here for the Excel Data File •-1. Use the appropriate statistical software to estimate a logistic regression model using Under Armour as the response variable and age as the predictor variable. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. 1 Purchase Age 234 1 39 0 28 0 30 5 0 34 69 1 43 7 1 34 8 0 37 Coefficient 9 0 21 Intercept Age 10 1 23 11 0 32 12 0 45 13 0 31 •-2. Compute the predicted probability of an Under Armour purchase for a 20-year-old customer and a 30-year-old customer. Note: Round coefficient estimates to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). 14 1 29 15 0 39 16 0 42 17 1 21 18 0 39 20-year-old customer 30-year-old customer 19 0 34 20 0 23 21 0 29 22 22 0 31 b-1. Select the null and the alternative hypotheses to test Annabel's belief that the Under Armour brand attracts a younger customer. 23 0 40 24 0 35 25 0 48 He: 61; HA: 61 < 0 He: 610; HA: 6₁ > 0 He: 61 ; HA: 61> 0 26 0 27 27 0 39 28 0 38 29 0 36 b-2. Find the p-value. O 0.02 s p-value < 0.05 30 0 31 31 1 17

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Annabel, a retail analyst, has been following Under Armour, Incorporated, the pioneer in the compression-gear market. Compression
garments are meant to keep moisture away from a wearer's body during athletic activities in warm and cool weather. Annabel believes
that the Under Armour brand attracts a younger customer relative to other companies. The accompanying file includes data on the age
of the customers and whether or not they purchased Under Armour (Purchase; 1 for purchase. 0 otherwise).
Click here for the Excel Data File
*-1. Use the appropriate statistical software to estimate a logistic regression model using Under Armour as the response variable and
age as the predictor variable.
Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.
Intercept
Age
Coefficient
a-2. Compute the predicted probability of an Under Armour purchase for a 20-year-old customer and a 30-year-old customer.
Note: Round coefficient estimates to at least 4 decimal places and final answers to 2 decimal places. Report the probability
between 0 and 1 (not in %).
20-year-old customer
30-year-old customer
b-1. Select the null and the alternative hypotheses to test Annabel's belief that the Under Armour brand attracts a younger customer.
He: 610; HA: 61 <0
He: B10; HA: 61 > 0
He: B₁ = 0; HA: 61 > 0
b-2. Find the p-value.
O 0.02 s p-value < 0.05
B
1 Purchase Age
2
1
39
3
0
28
4
0
30
5
0
34
6
1
43
7
1
34
8
0
37
9
0
21
10
1
23
11
0
32
12
0
45
13
0
31
14
1
29
15
0
39
16
0
42
17
1
21
18
0
39
19
0
34
20
0
23
21
0
29
22
0
31
23
0
40
24
0
35
25
0
48
26
0
27
27
0
39
28
0
38
29
0
36
30
0
31
31
1
17
Transcribed Image Text:Annabel, a retail analyst, has been following Under Armour, Incorporated, the pioneer in the compression-gear market. Compression garments are meant to keep moisture away from a wearer's body during athletic activities in warm and cool weather. Annabel believes that the Under Armour brand attracts a younger customer relative to other companies. The accompanying file includes data on the age of the customers and whether or not they purchased Under Armour (Purchase; 1 for purchase. 0 otherwise). Click here for the Excel Data File *-1. Use the appropriate statistical software to estimate a logistic regression model using Under Armour as the response variable and age as the predictor variable. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. Intercept Age Coefficient a-2. Compute the predicted probability of an Under Armour purchase for a 20-year-old customer and a 30-year-old customer. Note: Round coefficient estimates to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). 20-year-old customer 30-year-old customer b-1. Select the null and the alternative hypotheses to test Annabel's belief that the Under Armour brand attracts a younger customer. He: 610; HA: 61 <0 He: B10; HA: 61 > 0 He: B₁ = 0; HA: 61 > 0 b-2. Find the p-value. O 0.02 s p-value < 0.05 B 1 Purchase Age 2 1 39 3 0 28 4 0 30 5 0 34 6 1 43 7 1 34 8 0 37 9 0 21 10 1 23 11 0 32 12 0 45 13 0 31 14 1 29 15 0 39 16 0 42 17 1 21 18 0 39 19 0 34 20 0 23 21 0 29 22 0 31 23 0 40 24 0 35 25 0 48 26 0 27 27 0 39 28 0 38 29 0 36 30 0 31 31 1 17
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