Beverage Sales 3]Temperature Sales 85 1,8101 $4,825! | $ 8415 12131 15 5.2.3561
ID: 3222749 • Letter: B
Question
Beverage Sales 3]Temperature Sales 85 1,8101 $4,825! | $ 8415 12131 15 5.2.3561 12 S-4,930 | $.9,138/ 89 $2,7141 14 83 $ 1,082 1,290 i 82 s-894 | 91 $ 2,906; 22 79 S 462 >123 1 1 SI 24 .95 26 E 1 ... 58 51 010 4 400 i 20 002 15353266 3342 90 70 94 6 5 6 2 1 50 6 58280 0166-1:5 26329170298 9 61 409 B le T 4, -18-2 4921 13 2 4 1 15 asssssss $$$$$ $$$$ $ $ sss S--r 509246863 93-20-2-1 0 4 9 1:5 8978898 8009-8-7. | 9 9.8 8:00 a,8 9 9 8,7.. 8 9 234567890 11 2 3 4 5 6 7 8 90-12 34 56|789 12.2:2 2 2Explanation / Answer
Answer:
16). The model fit R square is
d). 0.947
17. The sales forecast for a temperature of 90 is
Predicted Sales = 142850.3-3643.2*90+23.3*90*90=3692.3
a). $3692
Regression Analysis
R²
0.947
Adjusted R²
0.942
n
21
R
0.973
k
2
Std. Error
635.137
Dep. Var.
sales
ANOVA table
Source
SS
df
MS
F
p-value
Regression
130,693,232.2313
2
65,346,616.1157
161.99
3.10E-12
Residual
7,261,171.0068
18
403,398.3893
Total
137,954,403.2381
20
Regression output
confidence interval
variables
coefficients
std. error
t (df=18)
p-value
95% lower
95% upper
Intercept
142,850.3406
30,575.7015
4.672
.0002
78,613.1753
207,087.5059
x
-3,643.1717
705.2304
-5.166
.0001
-5,124.8058
-2,161.5376
xx
23.3004
4.0532
5.749
1.89E-05
14.7849
31.8158
Regression Analysis
R²
0.947
Adjusted R²
0.942
n
21
R
0.973
k
2
Std. Error
635.137
Dep. Var.
sales
ANOVA table
Source
SS
df
MS
F
p-value
Regression
130,693,232.2313
2
65,346,616.1157
161.99
3.10E-12
Residual
7,261,171.0068
18
403,398.3893
Total
137,954,403.2381
20
Regression output
confidence interval
variables
coefficients
std. error
t (df=18)
p-value
95% lower
95% upper
Intercept
142,850.3406
30,575.7015
4.672
.0002
78,613.1753
207,087.5059
x
-3,643.1717
705.2304
-5.166
.0001
-5,124.8058
-2,161.5376
xx
23.3004
4.0532
5.749
1.89E-05
14.7849
31.8158
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