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The questions and answers for exam #3 of the stat303 course, which covers hypothesis testing and confidence intervals. Students are required to apply various statistical tests to determine if there is a significant difference between population means or proportions based on given data.
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A. Since it’s obvious that there are more purple than green, I can make that conclusion without running a hypothesis test. B. My p-value is 0.2186, so I would be unable to con- clude there are more purple than green. C. My p-value is 0.1093, so I would be unable to con- clude there are more purple than green. D. My p-value is 0.8907, so I would be unable to con- clude there are more purple than green. E. My p-value is 0.8907, so there are 89.07% more purples than greens.
A. H 0 : μ = 50 vs. HA : μ < 50 with a non-normal sample of size 50 B. H 0 : π = 0.5 vs. HA : π < 0 .5 with a sample of size 50 C. H 0 : π = 0.85 vs. HA : π < 0 .85 with a sample of size 50 D. H 0 : π 1 = π 2 vs. HA : π 1 < π 2 with independent samples of size 50 E. All of the above are valid z-tests.
A. when we want the most powerful 2-sample test B. when we have dependent samples C. when we have similar variances and equal samples sizes D. when we have equal sample sizes (we don’t need the variances to be the same) E. Two of the above are correct.
A. 0. B. 0. C. 0. 10 > p-value > 0. 05 D. 0. 20 > p-value > 0. 10 E. We don’t have a t-table for negative numbers, so we can’t say.
A. 3 and 0. B. 3 and 0. C. 3.14 and 0. D. 3.14 and 0. E. 3.14 and 0.
A. There really isn’t anything they can do; they sim- ply have to proceed with what the data give them. B. They might proceed as usual but alter the p-value later to compensate for the skewness in their data. C. They might use a non-parametric (NP) test pro- cedure. D. They might try a transform to the data so that it’s not skewed. E. Each of C and D above are possible approaches they might consider using.
A. a 1-sample test of means to see if the average di- vorce rate is different from the national average B. a 2-sample test of means to see if the average di- vorce rate is different for childless couples C. a paired t-test comparing husbands and wives D. a 1-sample test of proportions comparing her pro- portion of divorces with the national percent after five years of marriage E. a 2-sample test of proportions comparing the pro- portions of divorced couples with the proportion of those still married
A. The sample is not statistically significant at the 0.02 level. We cannot say the true mean is not 45. B. The sample mean is significantly different from μ = 45 at the 0.04 level since this is a two-sided test. C. There would be no reason to believe the selected students come from a different population. D. This suggests, at the 0.02 level, that there is ev- idence to conclude that the sample comes from a population with a mean different from μ = 45. E. This suggests, at the 0.01 level, that there is ev- idence to conclude that the sample comes from a population with a mean different from μ = 45.
A. The confidence interval would be longer and the p-value would decrease. B. The confidence interval would be shorter and the p-value would increase. C. The confidence interval would not change and the p-value also would not change. D. The confidence interval would be shorter and the p-value would decrease. E. The confidence interval would be shorter but the p-value would not change.
A. when it leads to non-practical significance B. when its greater than the sample size necessary for a given margin of error C. when it’s cost prohibitive D. All of the above are correct. E. more is always better
A. 0. 20 > p-value > 0. 10 B. 0. 10 > p-value > 0. 05 C. 0. 15 > p-value > 0. 10 D. 0. 30 > p-value > 0. 20 E. 0. 20 > p-value > 0. 15
A. At the 5% significance level, we would fail to prove that there is a difference between the two popula- tion means, μ 2 and μ 1. B. The margin of error for the difference between the two sample means would be smaller if we were to take larger samples. C. If a 99% confidence interval were calculated in- stead of the 95% interval, it would include more values for the difference between the two popula- tion means. D. The difference in the true means would be in the 95% confidence interval. E. All of the above are true statements about the data.
A. concluding that the true means were the same when they were actually different B. concluding that the true means were different when they were actually the same C. failing to conclude that the true means were the same when they were actually different D. failing to conclude that the true means were dif- ferent when they were actually the same E. failing to conclude that the true means were dif- ferent when they were actually were different
A. H 0 : μ ≤ 100 vs. HA : μ > 100 B. H 0 : μ ≥ 100 vs. HA : μ < 100 C. H 0 : μ = 100 vs. HA : μ 6 = 100 D. H 0 : μ < 100 vs. HA : μ ≥ 100 E. H 0 : μ > 100 vs. HA : μ ≤ 100
1C,2C,3B,4C,5A,6E,7D,8D,9A,10E,11D 12E,13C,14D,15E,16D,17A,18D,19B,20B