Predict the purchase amount in dollars if you know there are 31 items. Either show the work or provide a detailed explanation for how you used the regression equation to arrive at your answer.
. Predict the purchase amount in dollars if you know there are 31 items. Either show the work or provide a detailed explanation for how you used the regression equation to arrive at your answer.
|
Age |
Gender |
Height |
Arm Length |
Number Siblings |
Birth Order |
Handedness |
Number Classes |
Number Credits |
Hrs. Exercise |
Athlete at Broome |
Hrs. TV |
Award |
Pulse |
Number Piercings |
Facebook Friends |
Followers on Instagram |
Tattoo |
Division |
Local |
section |
|
18 |
f |
63 |
27.5 |
2 |
3 |
r |
4 |
14 |
1.5 |
n |
3 |
NP |
74 |
2 |
82 |
72 |
n |
HS |
y |
4 |
|
19 |
m |
74 |
31.5 |
4 |
5 |
r |
4 |
11 |
5 |
n |
1.5 |
O |
|
0 |
600 |
700 |
n |
STEM |
y |
4 |
|
17 |
f |
66 |
29.2 |
2 |
2 |
l |
6 |
15 |
5 |
y |
21 |
NP |
64 |
2 |
1801 |
1370 |
n |
HS |
y |
4 |
|
18 |
f |
66 |
30 |
5 |
5 |
r |
4 |
12 |
30 |
n |
15 |
NP |
91 |
1 |
500 |
700 |
n |
LA |
y |
4 |
|
30 |
m |
67 |
30 |
3 |
1 |
r |
4 |
12 |
5 |
n |
5 |
OG |
83 |
2 |
|
|
y |
STEM |
n |
4 |
|
20 |
f |
66 |
27 |
1 |
|
r |
5 |
15 |
7 |
n |
7 |
AA |
65 |
1 |
50 |
1015 |
n |
LA |
y |
4 |
|
26 |
f |
67 |
29 |
1 |
1 |
r |
5 |
14 |
3 |
n |
0 |
OG |
22 |
5 |
130 |
120 |
y |
HS |
y |
4 |
|
18 |
f |
64 |
28 |
1 |
2 |
r |
5 |
13 |
7 |
y |
6 |
NP |
20 |
5 |
50 |
50 |
y |
STEM |
y |
4 |
|
17 |
f |
64 |
28 |
3 |
2 |
r |
5 |
13 |
2 |
n |
3 |
NP |
|
9 |
407 |
472 |
n |
|
y |
4 |
|
19 |
m |
69 |
|
2 |
1 |
r |
5 |
13 |
1 |
n |
10 |
NP |
|
0 |
0 |
70 |
y |
STEM |
y |
4 |
|
18 |
f |
66 |
27.5 |
4 |
1 |
r |
5 |
12 |
|
n |
48 |
AA |
70 |
2 |
289 |
246 |
y |
HS |
n |
4 |
|
19 |
m |
75 |
30.5 |
3 |
2 |
r |
5 |
13 |
4 |
n |
2 |
OG |
86 |
0 |
254 |
317 |
n |
LA |
y |
4 |
|
18 |
m |
70 |
31 |
2 |
2 |
r |
4 |
14 |
1 |
n |
18 |
NP |
69 |
0 |
0 |
280 |
n |
HS |
n |
4 |
|
18 |
m |
73 |
30.5 |
2 |
2 |
r |
6 |
17 |
4 |
n |
6 |
NP |
|
0 |
0 |
1000 |
n |
|
n |
4 |
|
18 |
m |
70 |
31.5 |
2 |
2 |
r |
5 |
16 |
3 |
n |
40 |
OG |
71 |
0 |
300 |
0 |
n |
STEM |
n |
4 |
|
19 |
f |
68 |
29 |
2 |
2 |
r |
5 |
12 |
0 |
n |
4 |
OG |
|
2 |
0 |
1000 |
n |
|
n |
4 |
|
18 |
f |
64 |
27.5 |
3 |
4 |
r |
5 |
15 |
0 |
n |
10 |
OG |
92 |
9 |
200 |
400 |
y |
|
y |
4 |
|
18 |
m |
71 |
31.5 |
1 |
1 |
r |
4 |
12 |
3 |
y |
8 |
OG |
|
1 |
0 |
792 |
y |
BPS |
n |
4 |
|
19 |
m |
71 |
30 |
9 |
2 |
r |
6 |
15 |
10 |
n |
1 |
OG |
|
2 |
0 |
2000 |
y |
HS |
y |
4 |
|
24 |
m |
70 |
30 |
5 |
6 |
a |
1 |
3 |
3.5 |
n |
15.5 |
AA |
58 |
0 |
2000 |
450 |
n |
LA |
y |
12 |
|
21 |
m |
72 |
31 |
2 |
2 |
r |
5 |
15 |
5 |
n |
10 |
NP |
52 |
1 |
0 |
378 |
y |
BPS |
y |
12 |
|
18 |
m |
69 |
30 |
1 |
2 |
r |
7 |
20.5 |
5 |
n |
3 |
NP |
62 |
0 |
186 |
716 |
n |
HS |
n |
12 |
|
44 |
f |
64 |
25 |
5 |
2 |
r |
4 |
13 |
3 |
n |
3 |
NP |
65 |
6 |
500 |
25 |
y |
HS |
y |
12 |
|
18 |
f |
63 |
28 |
0 |
1 |
r |
4 |
14 |
15 |
n |
5 |
NP |
58 |
7 |
0 |
600 |
n |
HS |
y |
12 |
|
20 |
f |
66 |
29 |
1 |
2 |
r |
5 |
13 |
6 |
n |
5 |
OG |
62 |
4 |
200 |
1000 |
y |
HS |
n |
12 |
|
22 |
f |
68 |
30 |
1 |
2 |
r |
2 |
7 |
7 |
n |
20 |
AA |
68 |
0 |
0 |
0 |
n |
|
n |
12 |
|
18 |
f |
64 |
28 |
0 |
1 |
r |
6 |
18 |
7 |
n |
1 |
NP |
81 |
4 |
600 |
2000 |
y |
STEM |
n |
12 |
|
32 |
f |
63 |
26.5 |
2 |
1 |
r |
4 |
12 |
0 |
n |
7 |
NP |
|
5 |
1600 |
0 |
n |
HS |
y |
12 |
|
19 |
f |
67 |
27 |
4 |
1 |
r |
5 |
16 |
0 |
n |
2 |
NP |
88 |
4 |
923 |
1597 |
y |
HS |
n |
12 |
|
28 |
m |
66 |
29 |
5 |
2 |
r |
4 |
14 |
1 |
n |
20 |
NP |
70 |
0 |
250 |
0 |
y |
HS |
n |
12 |
|
19 |
f |
63 |
27 |
1 |
2 |
r |
6 |
17 |
6 |
y |
9 |
OG |
610 |
7 |
0 |
1500 |
n |
HS |
y |
12 |
|
18 |
f |
63 |
27 |
3 |
|
r |
5 |
15 |
7 |
y |
2 |
OG |
68 |
4 |
100 |
1000 |
y |
LA |
n |
12 |
|
19 |
f |
61.5 |
27 |
3 |
1 |
r |
5 |
14 |
2.5 |
y |
2.5 |
OG |
77 |
8 |
400 |
800 |
n |
HS |
y |
12 |
|
19 |
f |
66 |
28 |
1 |
1 |
r |
4 |
12 |
7 |
n |
12 |
NP |
70 |
5 |
150 |
900 |
n |
HS |
y |
12 |
|
19 |
f |
62 |
25.5 |
2 |
3 |
r |
4 |
12 |
0 |
n |
20 |
AA |
81 |
2 |
1000 |
340 |
n |
LA |
y |
12 |
|
21 |
f |
65 |
28 |
7 |
4 |
r |
4 |
12 |
6 |
unsure |
8 |
NP |
|
7 |
0 |
2000 |
y |
STEM |
y |
12 |
|
18 |
f |
68 |
29.5 |
1 |
2 |
l |
5 |
16 |
3 |
n |
5 |
OG |
45 |
2 |
0 |
65 |
n |
HS |
y |
12 |
|
20 |
f |
66 |
29.5 |
0 |
1 |
r |
5 |
13 |
0 |
n |
8 |
NP |
60 |
2 |
500 |
401 |
n |
LA |
n |
12 |
|
24 |
f |
68 |
28 |
0 |
1 |
r |
5 |
19 |
3 |
n |
3.5 |
AA |
86 |
2 |
0 |
62 |
y |
BPS |
n |
11 |
|
18 |
f |
64 |
29 |
1 |
1 |
r |
5 |
15 |
3 |
n |
7 |
NP |
75 |
2 |
120 |
1624 |
n |
LA |
n |
11 |
|
18 |
m |
71 |
33 |
0 |
1 |
r |
5 |
|
1 |
n |
4 |
AA |
74 |
0 |
0 |
30 |
n |
LA |
y |
11 |
|
19 |
f |
66 |
|
2 |
2 |
r |
5 |
16 |
2 |
n |
7 |
AA |
82 |
4 |
60 |
585 |
n |
BPS |
n |
11 |
|
19 |
f |
61 |
28 |
1 |
2 |
l |
4 |
12 |
0 |
n |
10 |
AA |
93 |
1 |
346 |
836 |
y |
HS |
n |
11 |
|
18 |
f |
69 |
29 |
1 |
2 |
l |
5 |
15 |
60 |
unsure |
14 |
AA |
104 |
4 |
2000 |
1000 |
y |
LA |
y |
11 |
|
18 |
f |
64 |
28.5 |
2 |
2 |
r |
5 |
15 |
4 |
n |
2 |
OG |
78 |
4 |
0 |
1580 |
y |
HS |
y |
11 |
|
19 |
f |
66 |
27 |
1 |
1 |
r |
5 |
13 |
3 |
n |
10 |
OG |
75 |
7 |
500 |
1200 |
y |
LA |
y |
11 |
|
18 |
f |
65 |
25.3 |
4 |
3 |
r |
5 |
15 |
14 |
n |
20 |
AA |
74 |
4 |
250 |
1800 |
y |
LA |
y |
11 |
|
20 |
f |
66 |
28.5 |
5 |
3 |
r |
5 |
15 |
0.5 |
n |
60 |
AA |
74 |
3 |
2000 |
500 |
y |
LA |
y |
11 |
|
20 |
m |
71 |
30 |
1 |
1 |
r |
7 |
17 |
8.5 |
n |
|
NP |
|
0 |
950 |
1112 |
n |
LA |
n |
11 |
|
19 |
f |
63 |
25 |
7 |
6 |
r |
4 |
12 |
7 |
n |
3 |
AA |
101 |
2 |
2000 |
1600 |
n |
LA |
y |
11 |
|
18 |
f |
63 |
26 |
8 |
7 |
r |
5 |
16 |
5 |
n |
2 |
OG |
70 |
6 |
500 |
730 |
y |
HS |
y |
11 |
|
21 |
m |
66 |
29 |
0 |
1 |
l |
4 |
14 |
10 |
n |
2 |
OG |
78 |
0 |
0 |
600 |
y |
STEM |
n |
11 |
|
22 |
f |
69 |
27 |
0 |
1 |
r |
2 |
8 |
5 |
n |
3 |
OG |
86 |
6 |
2000 |
1500 |
y |
HS |
y |
11 |
|
39 |
f |
64 |
25.5 |
6 |
6 |
r |
2 |
6 |
5 |
n |
10 |
NP |
80 |
2 |
50 |
0 |
y |
HS |
y |
11 |
|
20 |
f |
62 |
25 |
1 |
1 |
r |
4 |
14 |
20 |
n |
0 |
NP |
|
0 |
0 |
0 |
n |
LA |
y |
11 |
|
18 |
m |
67 |
28.5 |
5 |
2 |
r |
5 |
16 |
8 |
y |
0 |
NP |
65 |
2 |
350 |
955 |
y |
|
y |
11 |
|
18 |
f |
61 |
27 |
4 |
1 |
r |
5 |
15 |
14 |
unsure |
7 |
OG |
88 |
0 |
0 |
0 |
n |
HS |
y |
11 |
|
24 |
f |
62 |
27.5 |
7 |
5 |
r |
5 |
13 |
3 |
n |
5 |
OG |
76 |
0 |
1000 |
950 |
n |
HS |
y |
11 |
Given information:
The data represents the values of the variables x = items and y = price.
Trending now
This is a popular solution!
Step by step
Solved in 4 steps with 1 images
