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The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x<-rock$shape. Assume that the n area measurements x=(X₁, X2,...,xn) are a random sample from a population with true unknown mean and true unknown variance 2. Remember, let x be defined by x<-rock$shape. a) Calculate, n, the number of elements in x. 48 b) Calculate the sample standard deviation s, of x. c) Estimate true mean μ, using this data by calculating the sample mean. d) Calculate the sample variance of x. e) Calculate the interquartile range of x, using R. f) Calculate the 50th percentile of x using R. AFA g) Calculate a trimmed mean for x using R. h) Since the sample size is >30 we can create a confidence interval for using a normal critical value. If we want the confidence interval to be at the 94% level and we use a normal critical value, then what critical value should we use? i) Calculate a 94% confidence interval(using a normal critical value) for μ.

The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x<-rock$shape. Assume that the n area measurements x=(X₁, X2,...,xn) are a random sample from a population with true unknown mean and true unknown variance 2. Remember, let x be defined by x<-rock$shape. a) Calculate, n, the number of elements in x. 48 b) Calculate the sample standard deviation s, of x. c) Estimate true mean μ, using this data by calculating the sample mean. d) Calculate the sample variance of x. e) Calculate the interquartile range of x, using R. f) Calculate the 50th percentile of x using R. AFA g) Calculate a trimmed mean for x using R. h) Since the sample size is >30 we can create a confidence interval for using a normal critical value. If we want the confidence interval to be at the 94% level and we use a normal critical value, then what critical value should we use? i) Calculate a 94% confidence interval(using a normal critical value) for μ.

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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The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x<-rock$shape. Assume that the n area measurements x=(X₁, X₂,...,xn) are a random sample from a population with true unknown mean μ and true unknown variance 2. Remember, let x be defined by x<-rock$shape. a) Calculate, n, the number of elements in x. 48 b) Calculate the sample standard deviation s, of x. c) Estimate true mean μ, using this data by calculating the sample mean. d) Calculate the sample variance of x. e) Calculate the interquartile range of x, using R. f) Calculate the 50th percentile of x using R. g) Calculate a trimmed mean for x using R. 48 h) Since the sample size is >30 we can create a confidence interval for μ using a normal critical value. If we want the confidence interval to be at the 94% level and we use a normal critical value, then what critical value should we use? i) Calculate a 94% confidence interval(using a normal critical value) for μ.
Transcribed Image Text:The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x<-rock$shape. Assume that the n area measurements x=(X₁, X₂,...,xn) are a random sample from a population with true unknown mean μ and true unknown variance 2. Remember, let x be defined by x<-rock$shape. a) Calculate, n, the number of elements in x. 48 b) Calculate the sample standard deviation s, of x. c) Estimate true mean μ, using this data by calculating the sample mean. d) Calculate the sample variance of x. e) Calculate the interquartile range of x, using R. f) Calculate the 50th percentile of x using R. g) Calculate a trimmed mean for x using R. 48 h) Since the sample size is >30 we can create a confidence interval for μ using a normal critical value. If we want the confidence interval to be at the 94% level and we use a normal critical value, then what critical value should we use? i) Calculate a 94% confidence interval(using a normal critical value) for μ.
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