Question

Which statement is not true about the 95% confidence level?
5 point
Confidence intervals computed by using the same procedure will include the true
population value for 95% of all possible random samples taken from the population.
O
The procedure that is used to determine the confidence interval will provide an
interval that includes the population parameter with probability of 0.95.
O
The probability that the true value of the population parameter falls between the
bounds of an already computed confidence interval is roughly 95%.
If we consider all possible randomly selected samples of the same size from a
population, the 95% is the percentage of those samples for which the confidence
interval includes the population parameter.

Answer 1

Answer:

Explanation: which of the following is true about a 95% confidence interval of the mean: 95 out of 100 sample means will fall within the limits of the confidence interval. 95 out of 100 confidence intervals will contain the population mean. 95% of population means will fall within the limits of the confidence interval.

Answer 2

Literally, the confidence interval of a dataset gives the probability the value of a given parameter will fall within a range of value.

The statement that is not true about 95% confidence interval is option (c).

There are several confidence intervals. The most common intervals are:

• $90\%$ confidence interval
• $95\%$ confidence interval
• $99\%$ confidence interval

The name of these intervals does represent the probability that the value of a given parameter will fall within the range of values close to the mean.

Take for instance, the 95% confidence interval.

The 95% of 95% confidence interval does not mean that the probability that the value of a given parameter will fall within a range of value close to the mean will be 95% or close to 95% or roughly 95%.

This means that option (c) is not true about 95% confidence interval

Read more about confidence intervals at:

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