Suppose that​ 90% confidence interval for the difference between two​ proportions, p1-p2, is​ ( 0.013,​ 0.245). If we were testing the following​ hypotheses: H0:​ p1=p2 versus​ H1: p1≠p2 at the .10 significance level we would

Suppose a 95% confidence interval for the difference in test scores between Class 1 and Class 2 (in that order) is the following: 9 +/− 2. These results were based on independent samples of size 100 from each class. Now suppose you switch the order of Class 1 and Class 2 in your analysis but keep the data labeled correctly in terms of which class they came from. Which of the following statements is false? A) You can't do it this way. You'll get negative numbers for the difference in the means and/or negative numbers for the standard error. B) You are confident that the average for Class 2 is 7 to 11 points lower than for Class 1.    C) You are still confident that the classes have significantly different mean scores. D) Your 95% confidence interval will now be entirely negative: from −7 to −11.

Suppose we know that a confidence interval for a population proportion is (0.105,0.355), with a sample proportion of p̂=0.23. What is the margin of error?

Prof. Johnson conducts a hypothesis test on whether the proportion of all UBC students who bike to school (denoted as p) equals 30%. Specifically, Prof.Johnson has H0:p=0.3 versus HA:p≠0.3. He obtains a P-value of 0.01. On the other hand, Prof. Smith would like to test if there is sufficient evidence to support that p is greater than 0.3 at the 10% significance level. Based on Prof. Johnson's result, will the null hypothesis of Prof. Smith's test be rejected? A. There is insufficient information to tell.B. Yes.C. No.

If the p-value of a hypothesis test is equal to 0.035, then the null hypothesis will be rejected for which cases? SELECT ALL THAT APPLY.   a. for a significance level of 0.01   b. for a significance level of 0.10   c. for a significance level of 0.05   d. for a significance level of 0.02