Given that:
- The manufacturing process produces on average 3% defective items.
- The company ships 15 items in each box.
- It wishes to guarantee no more than 1 defective item per box.
You need to use the following Binomial Distribution Formula in order to find the probability that the box will fail to satisfy the guarantee:
![P(x)=(n!)/((n-x)!x!)p^x(1-p)^(n-x)](https://img.qammunity.org/2023/formulas/mathematics/college/lr8p834dhd5zif4qbq0fbgjq2vk05zfky5.png)
Where "n" is the number of trials, "x" is the number of successes desired, and "p" is the probability of getting a success in one trial.
In this case:
![\begin{gathered} n=15 \\ x=0,1 \\ p=3\text{ \%}=(3)/(100)=0.03 \end{gathered}](https://img.qammunity.org/2023/formulas/mathematics/college/m27uv4hppazmv36kfiaaj4vzgp98hrkjql.png)
Since It wishes to guarantee no more than 1 defective item per box, you can set up that:
![P(x\leq1)=(15!)/((15-0)!0!)(0.03)^0(1-0.03)^(15-0)+(15!)/((15-1)!1!)(0.03)^1(1-0.03)^(15-1)](https://img.qammunity.org/2023/formulas/mathematics/college/xnss5utd95uejpssvz1ilu4a2q65od75yy.png)
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