Bank B, customers may enter any one of three different lines that have formed at three teller windows. Answer the following questions. Bank A 6.6 5.4 6.7 5.7 6.8 6.2 Bank B 6.3 4.1 7.1 6.7 Construct a 95% confidence interval for the population standard deviation o at Bank A. min
Bank B, customers may enter any one of three different lines that have formed at three teller windows. Answer the following questions. Bank A 6.6 5.4 6.7 5.7 6.8 6.2 Bank B 6.3 4.1 7.1 6.7 Construct a 95% confidence interval for the population standard deviation o at Bank A. min
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![The image presents a dataset of waiting times (in minutes) of customers at two different banks, showcasing different queue systems. Bank A uses a single waiting line for three teller windows, while Bank B has three separate lines for each window.
### Waiting Times
#### Bank A:
- 6.3
- 6.6
- 6.7
- 6.7
- 7.1
- 7.3
- 7.4
- 7.8
- 7.8
#### Bank B:
- 4.1
- 5.4
- 5.7
- 6.2
- 6.7
- 7.8
- 7.8
- 8.6
- 9.2
- 10.0
### Statistical Analysis
**Construct a 95% Confidence Interval for the Population Standard Deviation:**
- **Bank A:**
- Interval: [ ] min < σ_Bank A < [ ] min
- (Round to two decimal places as needed.)
- **Bank B:**
- Interval: [ ] min < σ_Bank B < [ ] min
- (Round to two decimal places as needed.)
### Interpretation
Consider the confidence intervals constructed above. Do these intervals suggest a difference in the variation among waiting times? Determine whether the single-line system or the multiple-line system is a better arrangement based on the following options:
- **Option A:** The variation appears to be significantly lower with a single line system. The multiple-line system appears to be better.
- **Option B:** The variation appears to be significantly lower with a multiple-line system. The single-line system appears to be better.
- **Option C:** The variation appears to be significantly lower with a single line system. The single-line system appears to be better.
- **Option D:** The variation appears to be significantly lower with a multiple-line system. The multiple-line system appears to be better.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff4a4f967-2c76-4bed-bb86-95ccb6b747a5%2Fd823cd42-946e-44f7-bb61-447f6fa8dad2%2F3l8oq4l_processed.jpeg&w=3840&q=75)
Transcribed Image Text:The image presents a dataset of waiting times (in minutes) of customers at two different banks, showcasing different queue systems. Bank A uses a single waiting line for three teller windows, while Bank B has three separate lines for each window.
### Waiting Times
#### Bank A:
- 6.3
- 6.6
- 6.7
- 6.7
- 7.1
- 7.3
- 7.4
- 7.8
- 7.8
#### Bank B:
- 4.1
- 5.4
- 5.7
- 6.2
- 6.7
- 7.8
- 7.8
- 8.6
- 9.2
- 10.0
### Statistical Analysis
**Construct a 95% Confidence Interval for the Population Standard Deviation:**
- **Bank A:**
- Interval: [ ] min < σ_Bank A < [ ] min
- (Round to two decimal places as needed.)
- **Bank B:**
- Interval: [ ] min < σ_Bank B < [ ] min
- (Round to two decimal places as needed.)
### Interpretation
Consider the confidence intervals constructed above. Do these intervals suggest a difference in the variation among waiting times? Determine whether the single-line system or the multiple-line system is a better arrangement based on the following options:
- **Option A:** The variation appears to be significantly lower with a single line system. The multiple-line system appears to be better.
- **Option B:** The variation appears to be significantly lower with a multiple-line system. The single-line system appears to be better.
- **Option C:** The variation appears to be significantly lower with a single line system. The single-line system appears to be better.
- **Option D:** The variation appears to be significantly lower with a multiple-line system. The multiple-line system appears to be better.
Transcribed Image Text:This image contains a table of critical values for the Chi-Square distribution, which is commonly used in statistics to test hypotheses. The table organizes information according to degrees of freedom (df) and the area to the right of the critical value, represented by common significance levels (0.995, 0.99, 0.975, 0.95, 0.10, 0.05, 0.025, 0.01, 0.005).
Here's a detailed transcription of the table:
---
**Degrees of Freedom | Area to the Right of the Critical Value**
| df | 0.995 | 0.99 | 0.975 | 0.95 | 0.10 | 0.05 | 0.025 | 0.01 | 0.005 |
|----|-------|-------|-------|------|------|------|-------|------|-------|
| 1 | 0.000 | 0.000 | 0.001 | 0.004 | 2.706 | 3.841 | 5.024 | 6.635 | 7.879 |
| 2 | 0.010 | 0.020 | 0.051 | 0.103 | 4.605 | 5.991 | 7.378 | 9.210 | 10.597 |
| 3 | 0.072 | 0.115 | 0.216 | 0.352 | 6.251 | 7.815 | 9.348 | 11.345 | 12.838 |
| 4 | 0.207 | 0.297 | 0.484 | 0.711 | 7.779 | 9.488 | 11.143 | 13.277 | 14.860 |
| 5 | 0.412 | 0.554 | 0.831 | 1.145 | 9.236 | 11.070 | 12.833 | 15.086 | 16.750 |
| 6 | 0.676 | 0.872 | 1.237 | 1.635 | 10.645 | 12.592 | 14.449 | 16.812 | 18.548 |
| 7 | 0.989
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