Using numbers it helps label the rectangle
Answer:
If I were to be honest I think you did it perfectly
<h2>
Answer with explanation:</h2>
According to the Binomial probability distribution ,
Let x be the binomial variable .
Then the probability of getting success in x trials , is given by :
, where n is the total number of trials or the sample size and p is the probability of getting success in each trial.
As per given , we have
n = 15
Let x be the number of defective components.
Probability of getting defective components = P = 0.03
The whole batch can be accepted if there are at most two defective components. .
The probability that the whole lot is accepted :

∴The probability that the whole lot is accepted = 0.99063
For sample size n= 2500
Expected value : 
The expected value = 75
Standard deviation : 
The standard deviation = 8.53
NOT SHUUUUUUUUURRRRREEEEEEE
Answer:
Choice A
Step-by-step explanation: