5. Consider testing the hypothesis Ho : p = 0.5 vs. Ha : pメ0.5 using two...
Truth p ~ Two samples are drawn to test the hypothesis, Ho : p = 0.5 vs HA: p < 0.5. Both samples have the same size ni = n2 = 123. However, the samples yield different sample proportions. Consider the statement: Both samples will produce the same p-value for the hypothesis test above. Is this statement always true, sometimes true or never true?
In a hypothesis testing problem a researcher wants to test the hypothesis Ho 20 versus Ha 20 A sample of size 100 yielded a sample mean x = 19.25 and a sample standard deviation s 2.5. The P-value for the above test is 0013 .5000 0026 0147 0294
In a test of hypothesis Ho: P = .31 versus Ha: P > .31 at the 1% level of significance a sample size of 1560 produced a p-hat(sample proportion) value of .34 and a test statistic z = 2.59. The p-value (observed significance level) of the test is about A 0.010 B 0.005 C 0.350 D 0.310 E 0.995
A hypothesis test for a population proportion p is given below: Ho: p = 0.25 vs. Ha: p NE 0.25 (NE means not equal) For sample size n=100 and sample proportion p = 0.30, compute the value of the test statistic: 1.67 -1.12 0.04 1.15
If we are testing the hypothesis H0: p = 0.5 vs. H1: p > 0.5 where p represents the proportion of American adults who would not be concerned if NSA collected records of personal telephone calls. When would you conclude that the data provide enough evidence that the proportion of adults who would not be concerned is 0.5? A. Never B. When exactly half of the people in the sample say they would not be bothered. C. When the p-value...
A hypothesis testing: Ho : p=0.55 HA: p >0.55. We conduct a survey with sample size n =832 and have p =0.75. Find the test statistic z associated with the sample proportion. Note: 1- Only round your final answer to 2 decimal places. Enter your final answer with 2 decimal places.
Truth p ~ Two samples are drawn to test the hypothesis, H0: p = 0.5 vs HA: p <0.5H0: p = 0.5 vs HA: p <0.5 n1=n2=123n1=n2=123 Consider the statement: The samples will produce different p-values for the hypothesis test above. Is this statement always true, sometimes true or never true?
Suppose that you are testing the hypotheses Ho: p= 0.20 vs. HA, p 0.20. A sample of size 250 results in a sample proportion of 0.27 a) Construct a 95% confidence interval for p. b) Based on the confidence interval, can you reject Ho at a 0.05? Explain c) What is the difference between the standard error and standard deviation of the sample proportion? d) Which is used in computing the confidence interval? a) The 95% confidence interval for p...
Perform the following hypothesis test of a proportion: HO: p = 0.33 HA: p not equal to 0.33 The sample proportion is 0.31 based on a sample size of 100. Use a 10% significance level. A) What is the value of the test statistic? (Give answer rounded to 2 decimals) (be careful to make sure your + or - sign is correct) B) What is the p-value for the problem? C) should the null hypothesis be rejected? YES or NO
Suppose you are testing the hypotheses Ho : p=0.21 vs. p +0.21 with significance level a = 0.05. A sample size of 209 results in a sample proportion of 0.26. As you know, one way to address two-sided tests is to create confidence intervals. Construct the appropriate confidence interval for p that could be used to address the test and report the upper limit of the confidence interval. Note: 1- Only round your final answer to 2 decimal places. Enter...