Final answer:
The statement about sample size for control charts being dependent on inspection costs versus the expected cost of a Type II error is correct. This relationship is due to the need to balance the cost of errors with the cost of quality control measures such as inspection.
Step-by-step explanation:
The statement that the sample size chosen for control charts depends on the cost of inspection versus the expected cost of a Type II error is True. When designing control charts, both the probability of Type I error (incorrectly rejecting a true null hypothesis) and Type II error (failing to reject a false null hypothesis) need to be considered. The probability of a Type II error, represented as B or ß, is particularly important because it signifies the risk of concluding there is no difference or effect when there is one. In practice, minimizing these errors involves a trade-off between the costs of sampling (inspection) and the costs associated with the errors (e.g., production of defective items). Therefore, organizations must balance these factors to determine an appropriate sample size that minimizes overall costs while maintaining desired levels of error protection.
To explicitly address a concept from the student's question, power of the test is relevant as it is defined as 1 - ß. A higher power is desirable as it means a test is more likely to detect an effect when it actually exists. Sample size directly influences test power—larger sample sizes can reduce the likelihood of committing a Type II error, as a larger sample size increases the test's power.