A confidence interval is constructed for an unknown population proportion, p. A sample is collected, and the 95% confidence interval is calculated to be 0.39 ± 0.06. Based on this information, it is most accurate to say that there is approximately 95% confidence in the assertion that:

Using confidence interval concepts, it is found that we can be 95% sure that the true population proportion is within 6% of 39%.

A confidence interval is built from a sample, has bounds a and b, and has a confidence level of x%. The interpretation is that we are x% confident that the population mean is between a and b, or even within the margin of error of the proportion.

In this problem, interval within 0.06 of 39%, hence:

The interpretation is that we can be 95% sure that the true population proportion is within 6% of 39%.

A similar problem is given at link

There is 95% confidence that the true value of the population proportion is included in the interval (0.33, 0.45).

Step-by-step explanation:

The (1 - α)% confidence interval for population parameter implies that there is a (1 - α) probability that the true value of the parameter is included in the interval.

Or, the (1 - α)% confidence interval for the parameter implies that there is (1 - α)% confidence or certainty that the true parameter value is contained in the interval.

The 95% confidence interval for the population proportion is calculated to be 0.39 ± 0.06.

The interval is:

CI = (0.33, 0.45)

This confidence interval implies that, there is 0.95  probability that the true value of the population proportion is included in the interval (0.33, 0.45).

Or, there is 95% confidence that the true value of the population proportion is included in the interval (0.33, 0.45).

step-by-step explanation:

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