4. To test the null hypothesis that two population means satisfy u1 = 42 by using matched pairs with two samples of size n, we require that n > 30 andn< N/20. Our test statistic TS is where d is the average difference of the matched pairs – with all subtractions done in the same order: first sample data minus second sample data! – and where sa is the sample standard deviation of the differences. The degrees of freedom is dof = n– 1. (a) For a two-tailed test, we may compute ta/2 = ±InvT(a/2, dof) and check that the test-statistic falls in a tail. Or we may instead compute P = 2 tcdf (|TS|, ∞, dof) and check that P< a. Suppose our null hypothesis is the population means agree (4 = 42), that our sample size is n = 100, and that we find d = -1.33 and sd = 2.72. i. If we use a two-tailed test, what is our alternative hypothesis: µi + µ2 ? µ1 < µ2 ? or ui > µ2 ? ii. What would we conclude if we rejected the null hypothesis with a two-tailed test? iii. Can we reject the null hypothesis at level of significance a = 0.05, using a two-tailed test?

MATLAB: An Introduction with Applications
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4. To test the null hypothesis that two population means satisfy µ1 = µ2 by using matched pairs with two samples
of size n, we require that n > 30 and n < N/20. Our test statistic TS is
(#)
where d is the average difference of the matched pairs - with all subtractions done in the same order: first
sample data minus second sample data!
The degrees of freedom is do f = n – 1.
and where sa is the sample standard deviation of the differences.
(a) For a two-tailed test, we may compute ±ta/2 = ±InvT(a/2, dof) and check that the test-statistic falls in
a tail. Or we may instead compute P = 2 * tcdf (|TS|, 0, dof) and check that P < a. Suppose our null
hypothesis is the population means agree (u1 = µ2), that our sample size is n = 100, and that we find
d = -1.33 and sa = 2.72.
i. If we use a two-tailed test, what is our alternative hypothesis: µi # µ2 ? µ1 < µ2 ? or µ1 > µ2 ?
ii. What would we conclude if we rejected the null hypothesis with a two-tailed test?
iii. Can we reject the null hypothesis
level of significance a = 0.05, using a two-tailed test?
Transcribed Image Text:4. To test the null hypothesis that two population means satisfy µ1 = µ2 by using matched pairs with two samples of size n, we require that n > 30 and n < N/20. Our test statistic TS is (#) where d is the average difference of the matched pairs - with all subtractions done in the same order: first sample data minus second sample data! The degrees of freedom is do f = n – 1. and where sa is the sample standard deviation of the differences. (a) For a two-tailed test, we may compute ±ta/2 = ±InvT(a/2, dof) and check that the test-statistic falls in a tail. Or we may instead compute P = 2 * tcdf (|TS|, 0, dof) and check that P < a. Suppose our null hypothesis is the population means agree (u1 = µ2), that our sample size is n = 100, and that we find d = -1.33 and sa = 2.72. i. If we use a two-tailed test, what is our alternative hypothesis: µi # µ2 ? µ1 < µ2 ? or µ1 > µ2 ? ii. What would we conclude if we rejected the null hypothesis with a two-tailed test? iii. Can we reject the null hypothesis level of significance a = 0.05, using a two-tailed test?
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