4. To test the null hypothesis that two population means satisfy 41 = H2 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 dof = n– 1. and where sa is the sample standard deviation of the differences. (b) For a right-tailed test, we may compute to = -InvT(a,dof) and check that the test-statistic falls in the tail. Or we may instead compute P = tcdf (|T S|,0, dof), then check that P< a and TS > 0. Suppose our null hypothesis is the population means agree (µ1 = µ2), that our sample size is n = 500, and that we find d= -0.94 and sa = 2.81. i. If we use a right-tailed test, what is our alternative hypothesis: u1 + 42 ? u1 < µ2 ? or ui > 42 ? ii. What would we conclude if we rejected the null hypothesis with a right-tailed test? iii. Can we reject the null hypothesis at level of significance a = 0.05, using a right-tailed test? iv. Can we reject the null hypothesis at level of significance a = 0.01, using a right-tailed test?

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Solve questions 1 through 4 please
4. To test the null hypothesis that two population means satisfy Hi = #2 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! - and where sa is the sample standard deviation of the differences.
The degrees of freedom is dof = n – 1.
(b) For a right-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|, ∞, dof), then check that P < a and TS > 0. Suppose
our null hypothesis is the population means agree (µ̟ = µ2), that our sample size is n = 500, and that
we find d = -0.94 and sa = 2.81.
i. If we use a right-tailed test, what is our alternative hypothesis: µ1 # µ2 ? µ1 < µz ? or µı > µ2 ?
ii. What would we conclude if we rejected the null hypothesis with a right-tailed test?
iii. Can we reject the null hypothesis at level of significance a = 0.05, using a right-tailed test?
iv. Can we reject the null hypothesis at level of significance a = 0.01, using a right-tailed test?
Transcribed Image Text:4. To test the null hypothesis that two population means satisfy Hi = #2 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! - and where sa is the sample standard deviation of the differences. The degrees of freedom is dof = n – 1. (b) For a right-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|, ∞, dof), then check that P < a and TS > 0. Suppose our null hypothesis is the population means agree (µ̟ = µ2), that our sample size is n = 500, and that we find d = -0.94 and sa = 2.81. i. If we use a right-tailed test, what is our alternative hypothesis: µ1 # µ2 ? µ1 < µz ? or µı > µ2 ? ii. What would we conclude if we rejected the null hypothesis with a right-tailed test? iii. Can we reject the null hypothesis at level of significance a = 0.05, using a right-tailed test? iv. Can we reject the null hypothesis at level of significance a = 0.01, using a right-tailed test?
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