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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. O A. The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. O B. 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. O C. 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. O D. 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.

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. O A. The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. O B. 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. O C. 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. O D. 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.

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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**Educational Content on Interpreting Confidence Intervals** **Heading: Understanding Confidence Intervals in Data Analysis** When analyzing data, especially from samples, confidence intervals provide a range within which we can reasonably expect a population parameter to lie. In this example, data was gathered from a sample of airport data speeds measured in Mbps (megabits per second). **Data Summary:** - **Confidence Interval**: (13.05 Mbps, 22.15 Mbps) - **Mean of Sample (x̄)**: 17.598 Mbps - **Sample Standard Deviation (Sx)**: 16.01712719 Mbps - **Sample Size (n)**: 50 - **Confidence Level**: 95% **Interpretation Task:** We are tasked to choose the correct interpretation of the given confidence interval from a set of options. Let's examine the options: - **Option A**: The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. - **Option B**: 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. - **Option C**: 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. - **Option D**: 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. **Correct Answer:** - **Option D**: "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." This option correctly states the definition of a confidence interval. We use confidence intervals to estimate where the true population mean is likely to fall, with a specific confidence level, given the data from a random sample. By understanding this interpretation, students and researchers can better comprehend how data analysis is used to make inferences about larger populations from sample data.
Transcribed Image Text:**Educational Content on Interpreting Confidence Intervals** **Heading: Understanding Confidence Intervals in Data Analysis** When analyzing data, especially from samples, confidence intervals provide a range within which we can reasonably expect a population parameter to lie. In this example, data was gathered from a sample of airport data speeds measured in Mbps (megabits per second). **Data Summary:** - **Confidence Interval**: (13.05 Mbps, 22.15 Mbps) - **Mean of Sample (x̄)**: 17.598 Mbps - **Sample Standard Deviation (Sx)**: 16.01712719 Mbps - **Sample Size (n)**: 50 - **Confidence Level**: 95% **Interpretation Task:** We are tasked to choose the correct interpretation of the given confidence interval from a set of options. Let's examine the options: - **Option A**: The limits of 13.05 Mbps and 22.15 Mbps contain 95% of all of the data speeds at the airports. - **Option B**: 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. - **Option C**: 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. - **Option D**: 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. **Correct Answer:** - **Option D**: "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." This option correctly states the definition of a confidence interval. We use confidence intervals to estimate where the true population mean is likely to fall, with a specific confidence level, given the data from a random sample. By understanding this interpretation, students and researchers can better comprehend how data analysis is used to make inferences about larger populations from sample data.
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