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In one sample survey, the weight of a population was assumed to be normally dis- tributed. During one month of the survey the 95 % confidence interval for the average weight μ (kg) based on the collected data y of a sample size of n = © 200 was cal- culated to be [L(y), U(y)] = [61.5, 66.0]. Which of the following interpretations are wrong? Justify for the false claims why they are wrong. why they are wrong. a) The parameter μ is normally distributed. b) The ML estimator (Y) = Y for μ is normally distributed. c) For every parameter μ value it holds that Pμ(µ = [61.5, 66.0]) = 0.95. - d) For every parameter μ value it holds that Pμ(µ = [L(Y), U(Y)]) = 0.95. e) If the survey would be repeated monthly and similar 95% confidence intervals would be calculated (far) into the future, the parameter μ would fall within about 95% of those intervals. f) Looking at the monthly 95 % confidence intervals (far) into the future, the confidence interval would become more narrow over time.

In one sample survey, the weight of a population was assumed to be normally dis- tributed. During one month of the survey the 95 % confidence interval for the average weight μ (kg) based on the collected data y of a sample size of n = © 200 was cal- culated to be [L(y), U(y)] = [61.5, 66.0]. Which of the following interpretations are wrong? Justify for the false claims why they are wrong. why they are wrong. a) The parameter μ is normally distributed. b) The ML estimator (Y) = Y for μ is normally distributed. c) For every parameter μ value it holds that Pμ(µ = [61.5, 66.0]) = 0.95. - d) For every parameter μ value it holds that Pμ(µ = [L(Y), U(Y)]) = 0.95. e) If the survey would be repeated monthly and similar 95% confidence intervals would be calculated (far) into the future, the parameter μ would fall within about 95% of those intervals. f) Looking at the monthly 95 % confidence intervals (far) into the future, the confidence interval would become more narrow over time.

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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In one sample survey, the weight of a population was assumed to be normally dis- tributed. During one month of the survey the 95 % confidence interval for the average weight μ (kg) based on the collected data y of a sample size of n = © 200 was cal- culated to be [L(y), U(y)] = [61.5, 66.0]. Which of the following interpretations are wrong? Justify for the false claims why they are wrong. why they are wrong. a) The parameter μ is normally distributed. b) The ML estimator (Y) = Y for μ is normally distributed. c) For every parameter μ value it holds that Pμ(µ = [61.5, 66.0]) = 0.95. - d) For every parameter μ value it holds that Pμ(µ = [L(Y), U(Y)]) = 0.95. e) If the survey would be repeated monthly and similar 95% confidence intervals would be calculated (far) into the future, the parameter μ would fall within about 95% of those intervals. f) Looking at the monthly 95 % confidence intervals (far) into the future, the confidence interval would become more narrow over time.
Transcribed Image Text:In one sample survey, the weight of a population was assumed to be normally dis- tributed. During one month of the survey the 95 % confidence interval for the average weight μ (kg) based on the collected data y of a sample size of n = © 200 was cal- culated to be [L(y), U(y)] = [61.5, 66.0]. Which of the following interpretations are wrong? Justify for the false claims why they are wrong. why they are wrong. a) The parameter μ is normally distributed. b) The ML estimator (Y) = Y for μ is normally distributed. c) For every parameter μ value it holds that Pμ(µ = [61.5, 66.0]) = 0.95. - d) For every parameter μ value it holds that Pμ(µ = [L(Y), U(Y)]) = 0.95. e) If the survey would be repeated monthly and similar 95% confidence intervals would be calculated (far) into the future, the parameter μ would fall within about 95% of those intervals. f) Looking at the monthly 95 % confidence intervals (far) into the future, the confidence interval would become more narrow over time.
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