ch 5

In testing Ho: p1=p2 vs H1: p1>p2 the computed value of the test statistic was z0 = 2.0. The P-value for this test is less than 0.025.

True

In testing hypotheses to compare the means of two populations, it does not matter if the two populations have known but different variances.

True

Statistical tests and CIs on the difference in two proportions can be performed by using the normal approximation to the binomial distribution.

True

Tests of hypotheses and CIs on variances are more sensitive to the normality assumption that tests and CIs on means.

True

The F distribution is used to conduct hypothesis tests and construct confidence intervals about the variances of two independent normal populations.

True

The analysis of variance can be used to compare several means.

True

The assumptions for the two-sample pooled t-test for the difference in two means are that there are random samples from two independent normal populations with common but unknown variance.

True

The paired t-test should be considered when different experimental units are not very similar and at least two observations can be collected on each experimental unit.

True

The test statistic for Ho: var1=var2 is Fo=S^2 1/S^2 2 where the S^2 t are the sample variances of two random samples from independent normal populations.

True

If the sample size had been smaller, the power would have been smaller.

True

A 95% CI on the ratio of the variances of two independent normal populations is 0.5<var1/var2<6. Consequently, the null hypothesis Ho: var1=var2 is rejected at the five percent level of significance.

False

A smaller value for proportion 2 would have led to higher power.

False

If a 95% CI on the difference in two means is -9.4<mu1-mu2<3.2 you would have rejected the null hypothesis Ho: Xbar1=Xbar2 at the 0.05 level of significance.

False

If the standard deviation had been larger, the power would have been larger.

False

In the two-sample pooled t-test the pooled variance is computed by averaging the two individual sample variances.

False

The assumption of sampling from normal populations is very important for the validity of the t-test.

False

The number of degrees of freedom for the two-sample t-test are the same regardless of whether or not the two population variances are equal.

False

The test statistic in the analysis of variance has a chi-square distribution.

False

This is an appropriate statement of a statistical hypothesis:. Ho: Xbar1=Xbar2

False

When comparing the means of two independent normal populations, if the two population variances are unequal, the pooled t- test can still be used.

False

An F random variable is defined as the ratio of two independent chi-square random variables each divided by their numbers of degrees of freedom.

True

In a two-sample pooled t- test with 24 degrees of freedom, the computed value of the test statistic is t0 = 2.55. If the alternative hypothesis is two-sided, and if t0.1,24=1.32, t0.05,24=1.71, t0.025=24=2.06, t0.01,24=2.49, then the P-value of this test is:

P<0.02

A 95% confidence interval on the different in two means is 3<u1-u2<5 . Which of the following statements is false?

The null hypothesis in H0: u1#u2 vs H1: u1=u2 is rejected at the one percent level of significance.

A normal probability plot of the observations from both samples can be useful in verifying the assumptions for the two-sample t-test and in determining whether the assumption of equal variances is reasonable.

True

A randomized block design is used to eliminate the effect of a nuisance factor on the experimental results.

True

If Xbar1 and Xbar2 are the means of two random samples of sizes n1 and n2 from independent normal populations with means mu1 and mu2 and unknown but common variances, then the statistic T= has a t distribution with degrees of freedom:

n1+n2-2