A manufacturing company that produces laminate for countertops is interested in studying the relationship between the number of hours of training that an employee receives and the number of defects per countertop produced. Ten employees are randomly selected. The number of hours of training each employee has received is recorded and the number of defects on the most recent countertop produced is determined. The results are as follows.   Hours of Training Defects per Countertop 11 55 44 11 77 00 33 33 22 55 22 44 55 11 55 22 11 88 66 22 Copy Data  The estimated regression line and the standard error are given.   Defects per Countertop=6.717822−1.004950(Hours of Training)Defects per Countertop=6.717822−1.004950(Hours of Training) se=1.229787se=1.229787   Suppose a new employee has had 44 hours of training. What would be the 99%99% prediction interval for the number of defects per countertop? Round your answer to two decimal places.

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A manufacturing company that produces laminate for countertops is interested in studying the relationship between the number of hours of training that an employee receives and the number of defects per countertop produced. Ten employees are randomly selected. The number of hours of training each employee has received is recorded and the number of defects on the most recent countertop produced is determined. The results are as follows.
 

Hours of Training Defects per Countertop
11 55
44 11
77 00
33 33
22 55
22 44
55 11
55 22
11 88
66 22

Copy Data 
The estimated regression line and the standard error are given.
 

Defects per Countertop=6.717822−1.004950(Hours of Training)Defects per Countertop=6.717822−1.004950(Hours of Training)

se=1.229787se=1.229787
 
Suppose a new employee has had 44 hours of training. What would be the 99%99% prediction interval for the number of defects per countertop? Round your answer to two decimal places.
 
 
 

 

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