A television manufacturer claims that (at least) 90% of its TV sets will not need service during the first 3 years of operation. A consumer agency wishes to check this claim, so it obtains a random sample of n = 100 purchasers and asks each whether the set purchased needed repair during the first 3 years after purchase. Let p̂ be the sample proportion of responses indicating no repair (so that no repair is identified with a success). Let p denote the actual proportion of successes for all sets made by this manufacturer. The agency does not want to claim false advertising unless sample evidence strongly suggests that p < 0.9. The appropriate hypotheses are then H0: p = 0.9 versus Ha: p < 0.9. (a) In the context of this problem, describe Type I and Type II errors. (Select all that apply.) A Type II error would be not obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact less than 90% need no repair. A Type I error would be not obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact less than 90% need no repair. A Type I error would be obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact (at least) 90% need no repair. A Type II error would be obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact (at least) 90% need no repair. Discuss the possible consequences of each. (Select all that apply.) The consumer agency might take action against the manufacturer when in fact the manufacturer is at fault. The consumer agency might take action against the manufacturer when in fact the manufacturer is not at fault. The consumer agency would not take action against the manufacturer when in fact the manufacturer is making true claims about the reliability of the TV sets. The consumer agency would not take action against the manufacturer when in fact the manufacturer is making untrue claims about the reliability of the TV sets. (b) Would you recommend a test procedure that uses α = 0.10 or one that uses α = 0.01? Explain. Use α = 0.10, as making a Type I error involves not catching the manufacturer when they are at fault. Use α = 0.01, as making a Type I error involves taking action against the manufacturer when in fact the manufacturer is not at fault. Use α = 0.01, as making a Type II error involves taking action against the manufacturer when in fact the manufacturer is not at fault. Use α = 0.10, as making a Type II error involves not catching the manufacturer when they are at fault.
Compound Probability
Compound probability can be defined as the probability of the two events which are independent. It can be defined as the multiplication of the probability of two events that are not dependent.
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Probability theory is a branch of mathematics that deals with the subject of probability. Although there are many different concepts of probability, probability theory expresses the definition mathematically through a series of axioms. Usually, these axioms express probability in terms of a probability space, which assigns a measure with values ranging from 0 to 1 to a set of outcomes known as the sample space. An event is a subset of these outcomes that is described.
Conditional Probability
By definition, the term probability is expressed as a part of mathematics where the chance of an event that may either occur or not is evaluated and expressed in numerical terms. The range of the value within which probability can be expressed is between 0 and 1. The higher the chance of an event occurring, the closer is its value to be 1. If the probability of an event is 1, it means that the event will happen under all considered circumstances. Similarly, if the probability is exactly 0, then no matter the situation, the event will never occur.
A television manufacturer claims that (at least) 90% of its TV sets will not need service during the first 3 years of operation. A consumer agency wishes to check this claim, so it obtains a random sample of
n = 100
purchasers and asks each whether the set purchased needed repair during the first 3 years after purchase. Let p̂ be the sample proportion of responses indicating no repair (so that no repair is identified with a success). Let p denote the actual proportion of successes for all sets made by this manufacturer.
The agency does not want to claim false advertising unless sample evidence strongly suggests that
p < 0.9.
The appropriate hypotheses are then
H0: p = 0.9
versus
Ha: p < 0.9.
(a)
In the context of this problem, describe Type I and Type II errors. (Select all that apply.)
A Type II error would be not obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact less than 90% need no repair.
A Type I error would be not obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact less than 90% need no repair.
A Type I error would be obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact (at least) 90% need no repair.
A Type II error would be obtaining convincing evidence that less than 90% of the TV sets need no repair when in fact (at least) 90% need no repair.
Discuss the possible consequences of each. (Select all that apply.)
The consumer agency might take action against the manufacturer when in fact the manufacturer is at fault.
The consumer agency might take action against the manufacturer when in fact the manufacturer is not at fault.
The consumer agency would not take action against the manufacturer when in fact the manufacturer is making true claims about the reliability of the TV sets.
The consumer agency would not take action against the manufacturer when in fact the manufacturer is making untrue claims about the reliability of the TV sets.
(b)
Would you recommend a test procedure that uses α = 0.10 or one that uses α = 0.01? Explain.
Use α = 0.10, as making a Type I error involves not catching the manufacturer when they are at fault.
Use α = 0.01, as making a Type I error involves taking action against the manufacturer when in fact the manufacturer is not at fault.
Use α = 0.01, as making a Type II error involves taking action against the manufacturer when in fact the manufacturer is not at fault.
Use α = 0.10, as making a Type II error involves not catching the manufacturer when they are at fault.
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