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.
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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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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