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Researchers are concerned that an unhealthy salmon population in the Kayatoga River Valley would have devastating effects on local brown bear populations. To test the health of the salmon, the researchers weighed 5050 randomly collected specimens from the Kayatoga River. They calculated a 99%99\% confidence interval of for the mean weight of salmon in the Kayatoga River (in kilograms).\newlineIs the following conclusion valid?\newlineIf 100100 more samples are taken (with elements chosen randomly and independently), it is expected that exactly 9999 of them will each produce a 99%99\% confidence interval that contains its sample mean.\newlineChoices:\newline(A)yes\newline(B)no

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Q. Researchers are concerned that an unhealthy salmon population in the Kayatoga River Valley would have devastating effects on local brown bear populations. To test the health of the salmon, the researchers weighed 5050 randomly collected specimens from the Kayatoga River. They calculated a 99%99\% confidence interval of for the mean weight of salmon in the Kayatoga River (in kilograms).\newlineIs the following conclusion valid?\newlineIf 100100 more samples are taken (with elements chosen randomly and independently), it is expected that exactly 9999 of them will each produce a 99%99\% confidence interval that contains its sample mean.\newlineChoices:\newline(A)yes\newline(B)no
  1. Confidence Interval Misunderstanding: The statement is a common misunderstanding of confidence intervals. A 99%99\% confidence interval means that if we were to take many samples and calculate a confidence interval for each, 99%99\% of those intervals would contain the true population mean, not the sample mean.
  2. Population Mean vs Sample Mean: Since the conclusion states that 9999 out of 100100 additional samples will produce a 99%99\% confidence interval that contains its sample mean, this is incorrect. The confidence interval is about the population mean, not the sample mean.

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