HELP ASAP. info is given in the pic. 21) Provide a 95% confidence interval on the average delivery time for all shipments with a Distance of 675 miles. A) 2.97; 11.67 B) 3.73; 10.91 C) 6.22; 8.42 D) 6.41: 8.23 E) 0; 15.67 22) To determine if shipment 2 is an influential observation you test the hypothesis: Ho: Shipment 2 is ok versus Ha: Shipment 2 has too much leverage. What is the test statistic (i.e., the leverage) for this hypothesis test? A) 0.111 B) 0.3 C) 4.068 D) 0.161 E) 0.276 23) What proportion of the shipment to shipment variability in Time to deliver a shipment is explained by the linear relationship with Distance? A) 0.4790 B) 0.6921 C) 0.0007 D) 0.0214 E) 0.4501 Use this information and the excel output above for questions 24 and 25) below: The operations manager would like to determine if the increase in delivery time for each addition mile of distance is less than 0.03. To do this, the operations manager tests the hypothesis Ho: Boistance ≥ 0.03 versus Ha: Distance < 0.03 using a = 0.05. 24) What is the value of r, the test statistic? A) 1.62 B) 2.62 C) 2.35 D) -10.53 E) -1.62 25) What is the critical value for the hypothesis test? A) -2.878 B) -1.734 C) -2.101 D) -2.552 E) -1.65

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HELP ASAP. info is given in the pic.

21) Provide a 95% confidence interval on the average delivery time for all shipments with
a Distance of 675 miles.
A) 2.97; 11.67
B) 3.73; 10.91
C) 6.22; 8.42
D) 6.41: 8.23
E) 0; 15.67

22) To determine if shipment 2 is an influential observation you test the hypothesis:
Ho: Shipment 2 is ok
versus
Ha: Shipment 2 has too much leverage.
What is the test statistic (i.e., the leverage) for this hypothesis test?
A) 0.111
B) 0.3
C) 4.068
D) 0.161
E) 0.276

23) What proportion of the shipment to shipment variability in Time to deliver a shipment
is explained by the linear relationship with Distance?
A) 0.4790
B) 0.6921
C) 0.0007
D) 0.0214
E) 0.4501


Use this information and the excel output above for questions 24 and 25) below:
The operations manager would like to determine if the increase in delivery time for each
addition mile of distance is less than 0.03. To do this, the operations manager tests the
hypothesis Ho: Boistance ≥ 0.03 versus Ha: Distance < 0.03 using a = 0.05.
24) What is the value of r, the test statistic?
A) 1.62
B) 2.62
C) 2.35
D) -10.53
E) -1.62
25) What is the critical value for the hypothesis test?
A) -2.878
B) -1.734
C) -2.101
D) -2.552
E) -1.65

Use the following scenario when answering
questions 21)->25) on this page and the next page.
The operations manager of a trucking company is studying
the relationship between the distance a shipment must travel
and the delivery time (Time), in days, it takes the shipment
to arrive at its destination. The manager takes a random
sample of 20 recent shipments (Time and Distance
worksheet). The data, along with summary statistics, appear
in the table to the right. The operations manager uses excel
to fit a simple regression model using Distance as the
independent or X variable and Time as the dependent or Y
variable. The excel output appears below.
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
D: Distance
0.6921
0.4790
0.4501
2.0044
20
df
1
18
19
SS
66.5
72.3
138.8
Coefficients Standard Error
-7.1264
0.0214
3.8428
0.0053
MS
66.5
4.0
t Stat
-1.8545
4.0681
F
16.5
P-value
0.0801
0.0007
Shipment D: Distance
1
656
853
646
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Average
Std dev
Sum
Significance F
0.0007
783
610
841
785
639
762
762
862
679
835
607
665
647
685
720
652
828
725.9
87.5
14517
Time
5
14
6
11
8
PARANORMANDO BNG
10
9
9
10
9
7
5
13
3
8
7
10
8
6
10
8.4
2.7
168
(D-Dbar)^2
4,879.0
16,167.1
6,376.0
3,266.1
13,421.2
13,259.5
3,498.7
7,542.9
1,306.8
1,306.8
18,536.8
2,194.9
11,913.7
14,125.3
3,702.7
6,217.3
1,668.7
34.2
5,453.8
10,434.6
7,265.3
5,586.5
145,306.6
Transcribed Image Text:Use the following scenario when answering questions 21)->25) on this page and the next page. The operations manager of a trucking company is studying the relationship between the distance a shipment must travel and the delivery time (Time), in days, it takes the shipment to arrive at its destination. The manager takes a random sample of 20 recent shipments (Time and Distance worksheet). The data, along with summary statistics, appear in the table to the right. The operations manager uses excel to fit a simple regression model using Distance as the independent or X variable and Time as the dependent or Y variable. The excel output appears below. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept D: Distance 0.6921 0.4790 0.4501 2.0044 20 df 1 18 19 SS 66.5 72.3 138.8 Coefficients Standard Error -7.1264 0.0214 3.8428 0.0053 MS 66.5 4.0 t Stat -1.8545 4.0681 F 16.5 P-value 0.0801 0.0007 Shipment D: Distance 1 656 853 646 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Average Std dev Sum Significance F 0.0007 783 610 841 785 639 762 762 862 679 835 607 665 647 685 720 652 828 725.9 87.5 14517 Time 5 14 6 11 8 PARANORMANDO BNG 10 9 9 10 9 7 5 13 3 8 7 10 8 6 10 8.4 2.7 168 (D-Dbar)^2 4,879.0 16,167.1 6,376.0 3,266.1 13,421.2 13,259.5 3,498.7 7,542.9 1,306.8 1,306.8 18,536.8 2,194.9 11,913.7 14,125.3 3,702.7 6,217.3 1,668.7 34.2 5,453.8 10,434.6 7,265.3 5,586.5 145,306.6
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