Answer:
0.9726 = 97.26% approximate probability that X is at most 30
Step-by-step explanation:
Binomial probability distribution
Probability of exactly x sucesses on n repeated trials, with p probability.
Can be approximated to a normal distribution, using the expected value and the standard deviation.
The expected value of the binomial distribution is:

The standard deviation of the binomial distribution is:

Normal probability distribution
Problems of normally distributed distributions can be solved using the z-score formula.
In a set with mean
and standard deviation
, the zscore of a measure X is given by:

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
When we are approximating a binomial distribution to a normal one, we have that
,
.
11% of all steel shafts produced by a certain process are nonconforming but can be reworked (rather than having to be scrapped).
This means that 
Random sample of 200 shafts
This means that 
Mean and Standard deviation:


(a) What is the (approximate) probability that X is at most 30
Using continuity correction, this is
, which is the pvalue of Z when X = 30.5. So



has a pvalue of 0.9726.
0.9726 = 97.26% approximate probability that X is at most 30