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3. To test the null hypothesis that the population mean is u = Ho with a single sample of size n, we require (say) that n > 30. Our test statistic TS is where F is the sample mean and s is the sample standard deviation. The degrees of freedom is dof = n - 1. (b) For a left-tailed test, we may compute -ta = InvT(a, dof) and check that the test-statistic falls in the tail. Or we may instead compute P = tcdf(|TS|,00, dof), then check that P < a and TS < 0. Suppose our null hypothesis is the population mean is u = 99, that our sample size is n = 600, and that we find I = 100.27 and s = 14.38. i. If we use a left-tailed test, what is our alternative hypothesis: µ# 99 ? µ < 99 ? or u > 99 ? ii. Explain what we would conclude if we rejected the null hypothesis with a left-tailed test. iii. Can we reject the null hypothesis at level of significance a = 0.05, using a left-tailed test?

3. To test the null hypothesis that the population mean is u = Ho with a single sample of size n, we require (say) that n > 30. Our test statistic TS is where F is the sample mean and s is the sample standard deviation. The degrees of freedom is dof = n - 1. (b) For a left-tailed test, we may compute -ta = InvT(a, dof) and check that the test-statistic falls in the tail. Or we may instead compute P = tcdf(|TS|,00, dof), then check that P < a and TS < 0. Suppose our null hypothesis is the population mean is u = 99, that our sample size is n = 600, and that we find I = 100.27 and s = 14.38. i. If we use a left-tailed test, what is our alternative hypothesis: µ# 99 ? µ < 99 ? or u > 99 ? ii. Explain what we would conclude if we rejected the null hypothesis with a left-tailed test. iii. Can we reject the null hypothesis at level of significance a = 0.05, using a left-tailed test?

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
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3. To test the null hypothesis that the population mean is u = Ho with a single sample of size n, we require (say) that n> 30. Our test statistic TS is () where F is the sample mean and s is the sample standard deviation. The degrees of freedom is dof = n - 1. (b) For a left-tailed test, we may compute -ta = InvT(a, dof) and check that the test-statistic falls in the tail. Or we may instead compute P = tcdf(|TS|,0, dof), then check that P < a and TS < 0. Suppose our null hypothesis is the population mean is µ = 99, that our sample size is n = 600, and that we find * = 100.27 and s = 14.38. i. If we use a left-tailed test, what is our alternative hypothesis: µ # 99 ? µ < 99 ? or µ > 99 ? ii. Explain what we would conclude if we rejected the null hypothesis with a left-tailed test. iii. Can we reject the null hypothesis at level of significance a = 0.05, using a left-tailed test? iv. Can we reject the null hypothesis at level of significance a = 0.01, using a left-tailed test?
Transcribed Image Text:3. To test the null hypothesis that the population mean is u = Ho with a single sample of size n, we require (say) that n> 30. Our test statistic TS is () where F is the sample mean and s is the sample standard deviation. The degrees of freedom is dof = n - 1. (b) For a left-tailed test, we may compute -ta = InvT(a, dof) and check that the test-statistic falls in the tail. Or we may instead compute P = tcdf(|TS|,0, dof), then check that P < a and TS < 0. Suppose our null hypothesis is the population mean is µ = 99, that our sample size is n = 600, and that we find * = 100.27 and s = 14.38. i. If we use a left-tailed test, what is our alternative hypothesis: µ # 99 ? µ < 99 ? or µ > 99 ? ii. Explain what we would conclude if we rejected the null hypothesis with a left-tailed test. iii. Can we reject the null hypothesis at level of significance a = 0.05, using a left-tailed test? iv. Can we reject the null hypothesis at level of significance a = 0.01, using a left-tailed test?
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