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determined that e average weight X for a catfish is u=3.2 ounds with a standard deviation of a=0.8 und. Assuming the weights of catfish are rmally distributed, the probability P that a

determined that e average weight X for a catfish is u=3.2 ounds with a standard deviation of a=0.8 und. Assuming the weights of catfish are rmally distributed, the probability P that a

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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OOCOOO000 3E1. The owner of a fish market determined that the average weight X for a catfish is = 3.2 pounds with a standard deviation of a=0.8 pound. Assuming the weights of catfish are normally distributed, the probability P that a randomly selected catfish will weigh between 2 and 4.5 pounds is P = P(2< X <4.5)=_ 000000000 3E1. The standard error = (Where = √n a Standard Deviation, n = Sample Size) of the mean (a) is always larger than the standard deviation of the population. (9) increases as the sample size increases. (7) decreases as the sample size increases. (p) does not change but instead remains constant whenever the sample size increases or decreases. 0000000000 3E1. The Central Limit Theorem is important in statistics because (0) for a large n, it says the population is approximately normal. (e) for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population. (II) for any sized
Transcribed Image Text:OOCOOO000 3E1. The owner of a fish market determined that the average weight X for a catfish is = 3.2 pounds with a standard deviation of a=0.8 pound. Assuming the weights of catfish are normally distributed, the probability P that a randomly selected catfish will weigh between 2 and 4.5 pounds is P = P(2< X <4.5)=_ 000000000 3E1. The standard error = (Where = √n a Standard Deviation, n = Sample Size) of the mean (a) is always larger than the standard deviation of the population. (9) increases as the sample size increases. (7) decreases as the sample size increases. (p) does not change but instead remains constant whenever the sample size increases or decreases. 0000000000 3E1. The Central Limit Theorem is important in statistics because (0) for a large n, it says the population is approximately normal. (e) for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population. (II) for any sized
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