Given the 95% confidence interval for u (3.782, 4.978), what conclusion do you reach regarding μ the test of hypothesis Ho: μ is equal to 4 versus Ha: μ is not equal to 4? FAIL TO REJECT THE NULL at an alpha level of .05 O REJECT THE NULL at an alpha level of .05
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- We have created a 95% confidence interval for μ with the result (148, 196). What conclusion will we make if we test H0: μ = 190 vs. Ha:μ ≠ 190 at α = 5%? A. Reject the alternative hypothesis B. Reject the null hypothesis C. Fail to reject the null hypothesis D. Type I errorA 95% confidence interval for u was given as -5.65 < u < 2.61. What would a test for Ho : µ = 0 vs H1 : µ # 0 conclude? A. reject the null hypothesis at a = 0.05 and all smaller a B. fail to reject the null hypothesis at a = = 0.05 and all smaller a C. reject the null hypothesis at a = 0.05 and all larger a D. fail to reject the null hypothesis at a = - 0.05 and all largerYou test the following hypotheses: Ho: µ = 1000 Ha: u + 100O You calculate a test statistic z = -3.13. You should reject the null hypothesis at a 99% confidence level (alpha = .01). True False
- E mw According to a recent poll 57% of Americans would vote for stricter gun controls. If a random sample of 100 people results in 68 individuals who would vote for stricter gun control, test the null hypothesis tha the actual percentage is 57%. As The null and alternative hypotheses are: Ho: p = 0.57 versus Ha: p > 0.57. The lowest level of significance to reject the null hypothesis is: OA: 0.06 OB: 0.04 OC: 0.09 OD: 0.02 OE: 0.03You test the following hypotheses: Ho: µ = 10 Ha: µ + 10 You calculate a test statistic z = -3.25. True or False - You should reject the null hypothesis at a 90% confidence level (alpha = .10). True FalseWith H1: p # 0.3827, the test statistic is z = 2.324. For 0. 1 significance level what are the p-value and the conclusion about the null hypothesis? Correct answer is not listed 0.01005, Fail to reject HO 0.02011, Reject HO 0.01005. Reject HO 0.3827, Reject HO 0.3827, Fail to reject HO
- A test of Ho: p = 0.5 versus Ha: p > 0.5 has a test statistic of z = 2.19. What is the P-value for the test? If the alternative hypothesis were Ha: p ≠≠0.5, what would be the value of the P-value?The admission office needs your help to evaluate the following hypothesis: Ho: there is not a significant linear relationship between the two sections Against: HA: there is a significant linear relationship between the two sections 1. What is the calculated F statistics? (round to the nearest hundredth) 2. Evaluate the F calculated and indicate if you are going to reject or fail to reject the null hypothesis using an alpha = 0.05 (reject/fail to reject)The NAEP considers that a national average of 283 is an acceptable performance. Using α = .05, run a two-tail t-test for one sample to test Ho: µ=283 for the 2019 scores. Report the t-obt, df, and p-values. Would you reject the null hypothesis that the 2019 scores come from a population with average 283? If this is the case, does it come from a population from larger or smaller average?
- Suppose that we have a problem for which the null and alternative hypothesis are given by: H0: μ = 890. H1:μ ≠ 890. Is this a right-tailed test, left-tailed test, or two-tailed test. Find the z value based on a level of significance of α=.09.Two researchers conduct separate studies to test Ho: p=0.50 against Ha: p0.50, each with n = 400. Researcher A gets 225 observations in the category of interest, and p=225/400 =0.5625. Researcher B gets 227 in the category of interest, and p=227/400 = 0.5675. Complete parts (a) through (e) below. A ... OB. Hypothesis tests that produce similar P-values always have the same conclusion. OC. Hypothesis tests that result in the same conclusion do not necessarily have the same P-value. D. A difference in conclusions between two hypothesis tests does not necessarily mean that the test with the result that is deemed "statistically significant" is actually much more significant than the test with the result that is deemed "not statistically significant." d. From part a, part b, and part c, explain why important information is lost by reporting the result of a test as "P-value ≤0.05" versus "P-value > 0.05," or as "reject Ho" versus "Do not reject Ho," instead of reporting the actual P-value.…Data were collected from a random sample of eight patients currently undergoing treatment for hypertension. Each subject reported the average number of cigarettes smoked per day (NUMCIGS) and each was assigned a numerical value reflecting their risk of cardiovascular disease (RISKCVD) The risk assessments were computed by physicians and based on blood pressure, cholesterol level, and exercise status. The risk assessments ranged from 0 to 100, with higher values indicating increased risk. The data is in the table below and is posted in the Session 9 module as an excel file (a8_q1.xlsx). Subject NUMCIGS RISKCVD 1 12 2 2 20 3 50 4 8 68 12 75 6. 8. 7 2 10 20 80 Let X = NUMCIGS and Y = RISKCVD. Calculate the correlation coefficient. Round to the third decimal point (e.g. 100.1249 becomes 100.130).