# the magnitude

True or false? Consider a random sample of size n from an x distribution. For such a sample, the margin of error for estimating μ is the magnitude of the difference between x and μ.

False. By definition, the margin of error is the magnitude of the difference between x and σ.

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True. By definition, the margin of error is the magnitude of the difference between x and μ.

True. By definition, the margin of error is the magnitude of the difference between x and σ.

False. By definition, the margin of error is the magnitude of the difference between x and μ.

True or false? Every random sample of the same size from a given population will produce exactly the same confidence interval for μ.

True. Different random samples will produce the same x values, resulting in the same confidence intervals.

False. Different random samples may produce different x values, resulting in the same confidence intervals.

False. Different random samples may produce different x values, resulting in different confidence intervals.

True. Different random samples may produce different x values, resulting in different confidence intervals.

True or false? A larger sample size produces a longer confidence interval for μ.

False. As the sample size increases, the maximal error decreases, resulting in a shorter confidence interval.

True. As the sample size increases, the maximal error increases, resulting in a longer confidence interval.

True. As the sample size increases, the maximal error decreases, resulting in a longer confidence interval.

False. As the sample size increases, the maximal error increases, resulting in a shorter confidence interval.

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the magnitude was first posted on March 8, 2020 at 10:42 am.