Construct a 99% confidence interval for the population standard deviation o at Bank A. min < OBank A min (Round to two decimal places as needed.)

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### Analysis of Customer Waiting Times at Banks

The table below presents customer waiting times (in minutes) for two different banks. These times reflect the variations in service line structures at each bank.

#### Waiting Times for Customers

- **Bank A**: 6.3, 6.6, 6.7, 6.8, 7.1, 7.2, 7.5, 7.7, 7.7, 7.7
  - At Bank A, customers enter a single waiting line that feeds into three teller windows.

- **Bank B**: 4.2, 5.4, 5.8, 6.3, 6.6, 7.7, 7.7, 8.4, 9.4, 10.0
  - At Bank B, customers may enter any of three separate lines, each leading to a different teller window.

#### Statistical Analysis

To assess the consistency of waiting times, we will construct a 99% confidence interval for the population standard deviation of waiting times at Bank A. This interval will provide insight into the variability customers might expect.

- Use the provided chi-square critical values table to aid in the calculation.

#### Instructions

Calculate the confidence interval for the standard deviation (σ) at Bank A:

\[ \text{min} < \sigma_{\text{Bank A}} < \text{max} \]

- Results should be rounded to two decimal places as needed.

This analysis helps in understanding service efficiency and can guide improvements in customer experience strategies.
Transcribed Image Text:### Analysis of Customer Waiting Times at Banks The table below presents customer waiting times (in minutes) for two different banks. These times reflect the variations in service line structures at each bank. #### Waiting Times for Customers - **Bank A**: 6.3, 6.6, 6.7, 6.8, 7.1, 7.2, 7.5, 7.7, 7.7, 7.7 - At Bank A, customers enter a single waiting line that feeds into three teller windows. - **Bank B**: 4.2, 5.4, 5.8, 6.3, 6.6, 7.7, 7.7, 8.4, 9.4, 10.0 - At Bank B, customers may enter any of three separate lines, each leading to a different teller window. #### Statistical Analysis To assess the consistency of waiting times, we will construct a 99% confidence interval for the population standard deviation of waiting times at Bank A. This interval will provide insight into the variability customers might expect. - Use the provided chi-square critical values table to aid in the calculation. #### Instructions Calculate the confidence interval for the standard deviation (σ) at Bank A: \[ \text{min} < \sigma_{\text{Bank A}} < \text{max} \] - Results should be rounded to two decimal places as needed. This analysis helps in understanding service efficiency and can guide improvements in customer experience strategies.
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