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Refer to the accompanying data display that results from a sample of airport data speeds in Mbps. The results in the screen display are based on a 95% confidence level. Write a statement that correctly interprets the confidence interval. TInterval (13.046,22.15) x= 17.598 Sx = 16.01712719 n= 50 Choose the correct answer below.

Refer to the accompanying data display that results from a sample of airport data speeds in Mbps. The results in the screen display are based on a 95% confidence level. Write a statement that correctly interprets the confidence interval. TInterval (13.046,22.15) x= 17.598 Sx = 16.01712719 n= 50 Choose the correct answer below.

MATLAB: An Introduction with Applications
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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**Understanding Confidence Intervals in Airport Data Speeds** Refer to the accompanying data display that results from a sample of airport data speeds in Mbps. The results in the screen display are based on a 95% confidence level. Write a statement that correctly interprets the confidence interval. **Confidence Interval Results:** - TInterval: (13.046, 22.15) - Mean (x̄): 17.598 Mbps - Standard deviation (Sx): 16.01712719 Mbps - Sample size (n): 50 **Choose the correct answer below:** - **A.** The limits of 13.05 Mbps and 22.15 Mbps contain the true value of the mean of the population of all data speeds at the airports. - **B.** The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. - **C.** We have 95% confidence that the limits of 13.05 Mbps and 22.15 Mbps contain the true value of the mean of the population of all data speeds at the airports. - **D.** We have 95% confidence that the limits of 13.05 Mbps and 22.15 Mbps contain the sample mean of the data speeds at the airports. **Explanation of Graph/Diagram:** The information provided is a straightforward presentation of a confidence interval derived from a sample of data speeds measured at airports. The interval (13.046, 22.15) represents the range within which the true mean of the population is expected to fall with 95% confidence, based on the calculations using the sample data. This example serves to illustrate how statistical methods are used to estimate the characteristics of a larger population from which the sample was drawn, providing insights that inform decision-making processes in various applications, such as optimizing airport data systems.
Transcribed Image Text:**Understanding Confidence Intervals in Airport Data Speeds** Refer to the accompanying data display that results from a sample of airport data speeds in Mbps. The results in the screen display are based on a 95% confidence level. Write a statement that correctly interprets the confidence interval. **Confidence Interval Results:** - TInterval: (13.046, 22.15) - Mean (x̄): 17.598 Mbps - Standard deviation (Sx): 16.01712719 Mbps - Sample size (n): 50 **Choose the correct answer below:** - **A.** The limits of 13.05 Mbps and 22.15 Mbps contain the true value of the mean of the population of all data speeds at the airports. - **B.** The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. - **C.** We have 95% confidence that the limits of 13.05 Mbps and 22.15 Mbps contain the true value of the mean of the population of all data speeds at the airports. - **D.** We have 95% confidence that the limits of 13.05 Mbps and 22.15 Mbps contain the sample mean of the data speeds at the airports. **Explanation of Graph/Diagram:** The information provided is a straightforward presentation of a confidence interval derived from a sample of data speeds measured at airports. The interval (13.046, 22.15) represents the range within which the true mean of the population is expected to fall with 95% confidence, based on the calculations using the sample data. This example serves to illustrate how statistical methods are used to estimate the characteristics of a larger population from which the sample was drawn, providing insights that inform decision-making processes in various applications, such as optimizing airport data systems.
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