Consider a cylindrical engine part manufacturer that has designed a new machine to reduce the variance of the outside diameters of their product. A random sample of ? = 25 outside diameters produced by this machine has a mean of ?(x bar)= 3 and a variance of ?x2 = 0.00014. Assume that the population of all cylindrical engine part outside diameters that would be produced by the new machine is normally distributed, and let ?x 2, denote the variance of this population. Find a 95% confidence interval for ?2x

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Description: Consider a cylindrical engine part manufacturer that has designed a new machine to reduce the variance of the outside diameters of their product. A random sample of ? = 25 outside diameters produced by this machine has a mean of ?(x bar)= 3 and a var

It is given that n = 25, x bar = 3 and s2 = 0.00014.

Answered: Consider a cylindrical engine part…

Linear Algebra: A Modern Introduction

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ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

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Consider a cylindrical engine part manufacturer that has designed a new machine to reduce the variance of the outside diameters of their product. A random sample of ? = 25 outside diameters produced by this machine has a mean of ?(x bar)= 3 and a variance of ?x² = 0.00014. Assume that the population of all cylindrical engine part outside diameters that would be produced by the new machine is normally distributed, and let ?_x ², denote the variance of this population. Find a 95% confidence interval for ?²_x

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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