To compute the confidence interval for the mean number of visits per week, we use a normal distribution.
The margin of error is calculated using the formula:
\[
\text{Margin of Error} = \frac{Z \times \sigma}{\sqrt{n}}
\]
where:
- \( Z = 2.326 \) (Z-Score for 98% confidence level)
- \( \sigma = 1.9 \) (standard deviation)
- \( n = 231 \) (sample size)
Substituting the values, we find:
\[
\text{Margin of Error} = \frac{2.326 \times 1.9}{\sqrt{231}} \approx 0.291
\]
With the margin of error calculated, we can determine the confidence interval for the population mean number of visits per week:
\[
\text{Lower Bound} = \bar{x} - \text{Margin of Error} = 2.3 - 0.291 \approx 2.009
\]
\[
\text{Upper Bound} = \bar{x} + \text{Margin of Error} = 2.3 + 0.291 \approx 2.591
\]
Thus, with 98% confidence, the population mean number of visits per week is between \( 2.009 \) and \( 2.591 \).
If many groups of 231 randomly selected members are studied, about \( 98.0\% \) of these confidence intervals will contain the true population mean number of visits per week, while about \( 2.0\% \) will not.
- a. The distribution type used is a normal distribution.
- b. The population mean number of visits per week is between \( \boxed{2.009} \) and \( \boxed{2.591} \) visits.
- c. About \( \boxed{98.0\%} \) of these confidence intervals will contain the true population mean number of visits per week, and about \( \boxed{2.0\%} \) will not.