Obs vendor earnings age hours 1 21 2841 29 12 2 53 1876 21 8 3 60 2934 62 10 4 1
ID: 3132068 • Letter: O
Question
Obs
vendor
earnings
age
hours
1
21
2841
29
12
2
53
1876
21
8
3
60
2934
62
10
4
184
1552
18
10
5
263
3065
40
11
6
281
3670
50
11
7
354
2005
65
5
8
401
3215
44
8
9
515
1930
17
8
10
633
2010
70
6
11
677
3111
20
9
12
710
2882
29
9
13
800
1683
15
5
14
914
1817
14
7
15
997
4066
33
12
Earnings of Mexican street vendors. Detailed interviews were conducted with over 1,000 street vendors in the city of Puebla, Mexico, in order to study the factors influencing vendors’ incomes (World Development, February 1998). Vendors were defined as individuals working in the street, and included vendors with carts and stands on wheels and excluded beggars, drug dealers, and prostitutes. The researchers collected data on gender, age, hours worked per day, annual earnings, and education level. A subset of these data (STREETVEN) appears in the accompanying table.
A) Give the least squares prediction equation.
Obs
vendor
earnings
age
hours
1
21
2841
29
12
2
53
1876
21
8
3
60
2934
62
10
4
184
1552
18
10
5
263
3065
40
11
6
281
3670
50
11
7
354
2005
65
5
8
401
3215
44
8
9
515
1930
17
8
10
633
2010
70
6
11
677
3111
20
9
12
710
2882
29
9
13
800
1683
15
5
14
914
1817
14
7
15
997
4066
33
12
Explanation / Answer
Earnings of Mexican street vendors. Detailed interviews were conducted with over 1,000 street vendors in the city of Puebla, Mexico, in order to study the factors influencing vendors’ incomes (World Development, February 1998). Vendors were defined as individuals working in the street, and included vendors with carts and stands on wheels and excluded beggars, drug dealers, and prostitutes. The researchers collected data on gender, age, hours worked per day, annual earnings, and education level. A subset of these data (STREETVEN) appears in the accompanying table.
A) Give the least squares prediction equation.
Earnings = -20.352+13.3504*age+243.7145*hours
Regression Analysis
R²
0.582
Adjusted R²
0.513
n
15
R
0.763
k
2
Std. Error
547.737
Dep. Var.
earnings
ANOVA table
Source
SS
df
MS
F
p-value
Regression
5,018,231.5433
2
2,509,115.7717
8.36
.0053
Residual
3,600,196.1900
12
300,016.3492
Total
8,618,427.7333
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=12)
p-value
95% lower
95% upper
Intercept
-20.3520
652.7453
-0.031
.9756
-1,442.5619
1,401.8579
age
13.3504
7.6717
1.740
.1074
-3.3647
30.0656
hours
243.7145
63.5117
3.837
.0024
105.3343
382.0947
Regression Analysis
R²
0.582
Adjusted R²
0.513
n
15
R
0.763
k
2
Std. Error
547.737
Dep. Var.
earnings
ANOVA table
Source
SS
df
MS
F
p-value
Regression
5,018,231.5433
2
2,509,115.7717
8.36
.0053
Residual
3,600,196.1900
12
300,016.3492
Total
8,618,427.7333
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=12)
p-value
95% lower
95% upper
Intercept
-20.3520
652.7453
-0.031
.9756
-1,442.5619
1,401.8579
age
13.3504
7.6717
1.740
.1074
-3.3647
30.0656
hours
243.7145
63.5117
3.837
.0024
105.3343
382.0947
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