For the interval estimation of \( \mu \) when \( \sigma \) is known and the sample is large, the proper distribution to use is the- \( t \) distribution with \( n - 1 \) degrees of freedom.- normal distribution.- \( t \) distribution with \( n + 1 \) degrees of freedom.- \( t \) distribution with \( n \) degrees of freedom.

For the interval estimation of u when o is known and the sample is large, the proper distribution to use is the O t distribution with n 1 degrees of freedom. normal distribution. O t distribution with n + 1 degrees of freedom. t distribution with n degrees of freedom.

For the interval estimation of u when o is known and the sample is large, the proper distribution to use is the O t distribution with n 1 degrees of freedom. normal distribution. O t distribution with n + 1 degrees of freedom. t distribution with n degrees of freedom.

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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at Recall that to test a proportion, p, assuming all requirements are met, the z values will be calculated using the following formula, where r is the number of successes, n is the number of trials, p = - is the sample statistic, p is the population probability of %3D success, and q = 1 - p represents the population probability of failure. р - р z = pq In order to use the normal distribution to estimate the p distribution, the number of trials n should be sufficiently large so that both np > 5 and ng > 5. We will first check that these requirements are met. We have a random sample of 20 binomial trials resulting in 9 successes and we wish to test the claim that the population proportion of successes does not equal 0.50 using a significance level of 0.05. Therefore, we can define n, p, and q as follows. n = 20 20 p = 0.50 0.50 q = 1 - p = 0.50 0.50 Step 2 Now calculate np and ng for n = 20, p = 0.50, and q = 0.50. np = X (0.50) ng = 200 We conclude that since ---Select--- p…
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