Answer:
0.2345 = 23.45% probability that there are exactly 3 defective resistors in the sample
Explanation:
For each resistor, there are only two possible outcomes. Either they are defective, or they are not. The probability of a resistor being defective is independent of other resistors. So we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.
![P(X = x) = C_(n,x).p^(x).(1-p)^(n-x)](https://img.qammunity.org/2021/formulas/mathematics/college/mj488d1yx012m85w10rpw59rwq0s5qv1dq.png)
In which
is the number of different combinations of x objects from a set of n elements, given by the following formula.
![C_(n,x) = (n!)/(x!(n-x)!)](https://img.qammunity.org/2021/formulas/mathematics/college/qaowm9lzn4vyb0kbgc2ooqh7fbldb6dkwq.png)
And p is the probability of X happening.
8.7% of the resistors produced are defective.
This means that
![p = 0.0870](https://img.qammunity.org/2021/formulas/mathematics/college/sdhncwf1iblr8d51s17t27een9ctwivo49.png)
If a random sample of 34 resistors is taken, what is the probability that there are exactly 3 defective resistors in the sample?
This is P(X = 3) when n = 34. So
![P(X = x) = C_(n,x).p^(x).(1-p)^(n-x)](https://img.qammunity.org/2021/formulas/mathematics/college/mj488d1yx012m85w10rpw59rwq0s5qv1dq.png)
![P(X = 3) = C_(34,3).(0.087)^(3).(0.913)^(31) = 0.2345](https://img.qammunity.org/2021/formulas/mathematics/college/vzslemlmn3d9bqx0kaa1x5ah9z0owtlszd.png)
0.2345 = 23.45% probability that there are exactly 3 defective resistors in the sample