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A manufacturing process produces 6.4% defective items. What is the probability that in a sample of...

A manufacturing process produces 6.4% defective items. What is the probability that in a sample of 49 items:

a. 10% or more will be defective? (Round the z-value to 2 decimal places and the final answer to 4 decimal places.)

Probability            

b. less than 2% will be defective? (Round the z-value to 2 decimal places and the final answer to 4 decimal places.)

Probability            

c. more than 10% or less than 2% will be defective? (Round the z-value to 2 decimal places and the final answer to 4 decimal places.)

Probability          

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Answer #1

a)

population proportion ,p=   0.064                      
n=   49                      
                          
std error , SE = √( p(1-p)/n ) =    0.0350                      
                          
sample proportion , p̂ =   0.10                      
Z value=( p̂ - p )/SE= (   0.10   -   0.064   ) /    0.0350   = 1.03
P ( p̂ >    0.1   ) =P(Z > ( p̂ - p )/SE) =                  
                          
=P(Z >   1.030   ) =    0.1516 (answer)        
excel formula for probability from z score is =NORMSDIST(Z)                          

b)

population proportion ,p=   0.064                      
n=   49                      
                          
std error , SE = √( p(1-p)/n ) =    0.035                      
                          
sample proportion , p̂ =   0.02                      
Z value=( p̂ - p )/SE= (   0.020   -   0.064   ) /    0.035   =   -1.26
P ( p̂ <    0.020   ) =P(Z<( p̂ - p )/SE) =                  
                          
=P(Z <    -1.26 ) =    0.1041              
excel formula for probability from z score is =NORMSDIST(Z)  

c)

                       population proportion ,p=   0.064                      
                       n=   49                      
                                                  
                       std error , SE = √( p(1-p)/n ) =    0.0350                      
                                                  
                       we need to compute probability for                           
                       0.02   < p̂ <   0.10                  
                                                  
                       Z1 =( p̂1 - p )/SE= (   0.02   -   0.064   ) /    0.0350   =   -1.258
                       Z2 =( p̂2 - p )/SE= (   0.1   -   0.064   ) /    0.0350   =   1.030
P(   0.02   < p̂ <   0.1   ) =    P[( p̂1-p )/SE< Z <(p̂2-p)/SE ]    =P(    -1.258   < Z <   1.030   )          
                                                  
= P ( Z <   1.030   ) - P (    -1.258   ) =    0.8484   -   0.104   =   0.7443              

so, P(more than 10% or less than 2%) = P(p>0.10 or p<0.02) = 1 -   P(   0.02   < p̂ <   0.1   ) = 1 - 0.7443 = 0.2557(answer)

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