The null and alternative hypotheses for a test are given, as well as some information about the actual sample and the statistic that is computed for each randomization sample. Indicate where the randomization distribution will be centered. H0:μ1=μ2H0:μ1=μ2 vs Ha:μ1>μ2Ha:μ1>μ2 Sample: x_1=2.7x_1=2.7, x_2=2.2x_2=2.2 Randomization statistic: x_1−x_2x_1-x_2

Test the research hypothesis that there is a difference in weights between the two groups at the 0.05 significance level? Assume the equality of variance, adequate sample size, and normal distribution for both the groups to test the hypothesis. X1 = 200   X2 = 198   n1 = 17   n2 = 17   s1 = 2.45   s2 = 2.35 Please show all the necessary steps of hypothesis testing to answer this question.

Two different types of catalysts are used in a chemical process. We want to conduct a hypothesis test to see if there is a difference in the yields at 5% significance level. Assume both populations are normaly distributed. To this end, we collect a simple random sample from each process. Assume equal variances. = = n-11, n=13,x,-90, x 91.4, 8, 4, 8=4.5

Explain the circumstances under which we would need to pool the variance for an independent samples t-test

Which would be the appropriate way to test differences in proportions for more than two samples?     t-test if variance is unknown     z-test     paired t-test     F-test for equality of variances     cross-tabulation procedure to conduct a chi-square test

In a hypothesis test for the population variance, the alternate hypothesis is the population variance doesn't equal 17.0. The significance level to be used is 0.05 and the sample size to be taken is 25. The table value(s) to use from the chi-square distribution is/are     12.401 and 39.364. 13.181 39.364 40.671

A researcher wants to measure average cardiovascular health of university students and compare those scores to the average scores in the general population. Assuming that population variance is known, what statistical test is most appropriate for this study?        independent-samples t-test     single-sample t-test     z-test for sample mean     related-samples t-test

Listed below are systolic blood pressure measurements (mm Hg) taken from the right and left arms of the same woman. Assume that the paired sample data is a simple random sample and that the differences have a distribution that is approximately normal. Use a 0.10 significance level to test for a difference between the measurements from the two arms. What can be concluded? Right arm Left arm 143 179 OA. Ho: H0 H₁: Hd=0 OC. Ho: P = 0 H₁: Hd 0 sufficient evidence to support the claim of a difference in measurements between the two arms.

An HIV clinical trial with 1151 subjects was conducted. We will focus on two variables from this trial: IVDrug and Age. IVDrug is a categorical variable that indicates whether each subject never, previously, or currently uses IV drugs. Age lists the subject's age in year. Thus, we have age for subjects in three treatment groups. Assume that the samples were collected independently and come from a normally distributed population with equal variances. An ANOVA is used to test whether average age in the three IV drug groups is the same. A partially filled-in ANOVA table is listed below. Use a significance level of 0.05. p-value Treatment Error Total df SS MS 76.77 F 7.5586

Determine your test statistic: either use a z-test or t-test• There are three key questions to ask:ƒ Is the variance of the population known?ƒ Is the distribution of the population normal (or approx. normal)?ƒ Is the sample size large?1. When the variance is known and either the distribution is normal or sample size is large,use a z-test statistic2. When the variance is unknown and a sample size less than 30, use a t-test statistic aslong as the population is normal (or approx. normal)?