A UPS efficiency expert is interested in finding out if the years of driving experience (EXP) can be used to predict the frequency of late deliveries (LATE). Here are the data (late deliveries are per 100 ): EXP ZEXP LATE ZLATE 16 0.49 8 0.43 19 1.34 10 1.45 15 0.21 7 -0.09 15 0.21 8 0.43 14 -0.07 6 -0.60 15 0.21 8 0.43 13 -0.35 5 -1.11 12 -0.64 5 -1.11 4 -2.90 3 -2.14 15 0.21 8 0.43 16 0.49 9 0.94 17 0.78 9 0.94 MEXP = 14.25 SDEXP = 3.54 MLATE= 7.17 SDLATE = 1.95 Use α = .05 for all decisions. Determine how many late deliveries (per 100) we would predict for a driver with 20 years of experience. No explanation is required – just report the predicted value as your final answer.
A UPS efficiency expert is interested in finding out if the years of driving experience (EXP) can be used to predict the frequency of late deliveries (LATE). Here are the data (late deliveries are per 100 ): EXP ZEXP LATE ZLATE 16 0.49 8 0.43 19 1.34 10 1.45 15 0.21 7 -0.09 15 0.21 8 0.43 14 -0.07 6 -0.60 15 0.21 8 0.43 13 -0.35 5 -1.11 12 -0.64 5 -1.11 4 -2.90 3 -2.14 15 0.21 8 0.43 16 0.49 9 0.94 17 0.78 9 0.94 MEXP = 14.25 SDEXP = 3.54 MLATE= 7.17 SDLATE = 1.95 Use α = .05 for all decisions. Determine how many late deliveries (per 100) we would predict for a driver with 20 years of experience. No explanation is required – just report the predicted value as your final answer.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 23PPS
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Question
A UPS efficiency expert is interested in finding out if the years of driving experience (EXP) can be used to predict the frequency of late deliveries (LATE). Here are the data (late deliveries are per 100 ):
|
EXP |
ZEXP |
LATE |
ZLATE |
|
16 |
0.49 |
8 |
0.43 |
|
19 |
1.34 |
10 |
1.45 |
|
15 |
0.21 |
7 |
-0.09 |
|
15 |
0.21 |
8 |
0.43 |
|
14 |
-0.07 |
6 |
-0.60 |
|
15 |
0.21 |
8 |
0.43 |
|
13 |
-0.35 |
5 |
-1.11 |
|
12 |
-0.64 |
5 |
-1.11 |
|
4 |
-2.90 |
3 |
-2.14 |
|
15 |
0.21 |
8 |
0.43 |
|
16 |
0.49 |
9 |
0.94 |
|
17 |
0.78 |
9 |
0.94 |
MEXP = 14.25 SDEXP = 3.54 MLATE= 7.17 SDLATE = 1.95
Use α = .05 for all decisions. Determine how many late deliveries (per 100) we would predict for a driver with 20 years of experience. No explanation is required – just report the predicted value as your final answer.
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