A parachute manufacturer is concerned that the failure rate of 0.1% advertised by his company may in fact be higher. A hypothesis test was run and the result was a P-value of 0.011. The most likely conclusion the manufacturer might make is:(a) My parachutes are safer than I claim.(b) My parachutes are not as safe as I claim them to be.(c) I can make no assumption of safety based on a statistical test.(d) The probability of a parachute failure is 0.011.(e) Both (b) and (d) are true.

b) My parachutes are not as safe as I claim them to be.

Step-by-step explanation:

Hypothesis test is a statistical test carried out by using experimental data (sample data).

A p-value is used to help check the statistical significance in the hypothesis test. If a p-value is less than 0.05, the null hypothesis is rejected, but if it is greater or equal to 0.05, we will fail to reject the null hypothesis.

In this case since the p-value(0.011) is very low, i.e less than 0.05(significance level), we can say that the null hypothesis is rejected. Which means that the manufacturer initial claim that his parachute is safe is wrong and the correct option here is that his parachute is not as safe as he claims.