The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 497 psi.In USE SALT(a) What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 and 10,200? (Round your answer to four decimal places.)(b) If the sample size had been 15 rather than 40, could the probability requested in part (a) be calculated from the given information? Explain your reasoning.Yes, the probability in part (a) can still be calculated from the given information.No, n should be greater than 30 in order to apply the Central Limit Theorem.No, n should be greater than 20 in order to apply the Central Limit Theorem.No, n should be greater than 50 in order to apply the Central Limit Theorem.

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Description: The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 497 psi.In USE SALT(a) What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 and 10,200? (Round yo

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(a) What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 and 10,200? (Round your answer to four decimal places.)

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Concept explainers

Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.

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Question

The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 497 psi.
In USE SALT
(a) What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 and 10,200? (Round your answer to four decimal places.)
(b) If the sample size had been 15 rather than 40, could the probability requested in part (a) be calculated from the given information? Explain your reasoning.
Yes, the probability in part (a) can still be calculated from the given information.
No, n should be greater than 30 in order to apply the Central Limit Theorem.
No, n should be greater than 20 in order to apply the Central Limit Theorem.
No, n should be greater than 50 in order to apply the Central Limit Theorem.

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