Quiz 10.02 | Point Estimators – Stats Doesnt Suck

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Question 1 of 5

1. Question
A point estimator is defined as:
- a range of values that estimates an unknown population parameter.
- a range of values that estimates an unknown sample statistic.
- a single value that estimates an unknown population parameter.
- a single value that estimates an unknown sample statistic.
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Question 2 of 5

2. Question
The problem with relying on a point estimate of a population parameter is that:
- it is virtually certain to be wrong.
- it doesn't have the capacity to reflect the effects of larger sample sizes.
- it doesn't tell us how close or far the point estimate might be from the parameter.
- All of these choices are true.
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Question 3 of 5

3. Question
What does it mean for a point estimator to be unbiased?
- a) It always overestimates the population parameter.
- b) It always underestimates the population parameter.
- c) It overestimates and underestimates the population parameter equally.
- d) It always accurately estimates the population parameter.
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Question 4 of 5

4. Question
What does it mean for a point estimate to be consistent?
- a) The point estimator is always correct.
- b) The point estimator becomes more accurate as the sample size increases.
- c) The point estimator becomes less accurate as the sample size increases.
- d) The point estimator remains the same regardless of the sample size.
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Question 5 of 5

5. Question
What is relative efficiency in the context of point estimation?
- a) The point estimator is always efficient.
- b) The point estimator is chosen based on the lowest variation.
- c) The point estimator is chosen based on the highest variation.
- d) The point estimator is chosen based on the sample size.
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Quiz 10.02 | Point Estimators

Quiz 10.02 | Point Estimators

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