The target specification for the nominal distance between faces on the hexagonal bolt head is inches. The company has a goal that this new process will produce bolts with a tolerance of inches on this dimension, meaning the bolts produced will have a dimension between and inches. The "Three Sigma" approach to statistical quality assurance states that of the bolts will satisfy this criterion if the mean of a sample of bolts is equal to inches and three times the standard deviation is less than or equal to the tolerance. In other words, if $($where is the standard deviation of the sample$)$ then the new process will achieve this goal.

Code has already been provided to define the sampleMeasurements that is a row vector of measurements of sample bolts collected from a manufacturing run. Add code to the script to perform the following tasks using the data in the input vector and assign the results to the indicated variable names.

Compute the mean of the values in sampleMeasurements and assign this value to the variable sampleMean.

Compute the $"3$ sigma" value $($i$.$e$.$ three times the standard deviation$)$ for the data in sampleMeasurements and assign this value to the output variable sample$3$sigma.

Use appropriate built$-$in functions for these calculations $($again$,$ do not use a loop in your solution $-$ points will be lost if you use these.$).$ Note the variable sampleMeasurements is assigned values already. Do not overwrite these values in your code.