Question

True or False: Suppose we use a t-test for one population mean to test H0: μ...

True or False: Suppose we use a t-test for one population mean to test H0: μ = 3418 g and we reject H0 at α =.05, two-tailed. When we state that the hypothesis test result is "statistically significant at the 5% level", we mean that (mark each statement as true or false):

A) There is a 5% (long-term) chance that the decision to reject Ho is incorrect

B) There is strong evidence against the null hypothesis

C) The study did not have sufficient statistical power

D) If the null hypothesis is false, we would expect to obtain a test statistic as extreme or more extreme by chance alone in approximately 5 samples per each 100 random samples

E) The observed difference between x̅ and μ0 is definitely important clinically

Homework Answers

Answer #1

A. True. It is called Type I error in hypothesis testing. In this example, there is a 5% or less than 5% chance of rejecting the fact that the mean value is equal to 3418g.

B. True. 95% of the samples will not have the mean value equal to 3418g. It will be significantly higher or lower than the mean value of null hypothesis claim.

C. False. The probability of accepting null hypothesis when alternative hypothesis is true. Since the test is statistically significant at alpha = 0.05 level, probability of observing the H0 is less than 5%. This test has a sufficient statistical power.

D. False. Since the null is false, we will have 95 samples per 100 random samples with more extreme values.

E. True. If Sample mean differs from population parameter, then it is very important unbiased point estimation

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
If the null hypothesis is H0: μ ≥ 1250, then we have a left-tailed test. True...
If the null hypothesis is H0: μ ≥ 1250, then we have a left-tailed test. True of False
1. a) For a test of H0 : μ = μ0 vs. H1 : μ ≠...
1. a) For a test of H0 : μ = μ0 vs. H1 : μ ≠ μ0, the value of the test statistic z obs is -1.46. What is the p-value of the hypothesis test? (Express your answer as a decimal rounded to three decimal places.) I got 0.101 b) Which of the following is a valid alternative hypothesis for a one-sided hypothesis test about a population mean μ? a μ ≠ 5.4 b μ = 3.8 c μ <...
1) Consider a test of H0 : μ = μ0 vs. H0 : μ < μ0....
1) Consider a test of H0 : μ = μ0 vs. H0 : μ < μ0. Suppose this test is based on a sample of size 8, that σ2 is known, and that the underlying population is normal. If a 5% significance level is desired, what would be the rejection rule for this test? Reject H0 if zobs < -1.645 Reject H0 if tobs < -1.894 Reject H0 if zobs < -1.960 Reject H0 if tobs < -2.306 2) Which...
Which of the following is a benefit to using a one-tailed t-test (as opposed to a...
Which of the following is a benefit to using a one-tailed t-test (as opposed to a two-tailed test)? A) It improves the predictive power of the independent samples t-test. B) It reduces the impact of within-groups variance. C) We are more likely to reject the null hypothesis when the null hypothesis is false. D) We are less likely to reject the null hypothesis when the null hypothesis is false.
1. For a particular scenario, we wish to test the hypothesis H0 : μ = 14.9....
1. For a particular scenario, we wish to test the hypothesis H0 : μ = 14.9. For a sample of size 35, the sample mean X̄ is 12.7. The population standard deviation σ is known to be 8. Compute the value of the test statistic zobs. (Express your answer as a decimal rounded to two decimal places.) 2. For a test of H0 : μ = μ0 vs. H1 : μ ≠ μ0, assume that the test statistic follows a...
1. The P-value of a test of the null hypothesis is a. the probability the null...
1. The P-value of a test of the null hypothesis is a. the probability the null hypothesis is true. b. the probability the null hypothesis is false. c. the probability, assuming the null hypothesis is false, that the test statistic will take a value at least as extreme as that actually observed. d. the probability, assuming the null hypothesis is true, that the test statistic will take a value at least as extreme as that actually observed. 2. The P-value...
3. There is a different t distribution for every hypothetical sample size. True or False 2....
3. There is a different t distribution for every hypothetical sample size. True or False 2. For a chi-square test, if the observed number of cases in your sample fits what you expect given your knowledge of the population, you would reject the null hypothesis. True or False 1. A two-tailed hypothesis will have more statistical power than a one-tailed hypothesis. True or False
For the following hypothesis test, where H0: μ ≤ 10; vs. HA: μ > 10, we...
For the following hypothesis test, where H0: μ ≤ 10; vs. HA: μ > 10, we reject H0 at level of significance α and conclude that the true mean is greater than 10, when the true mean is really 14. Based on this information, we can state that we have: Made a Type I error. Made a Type II error. Made a correct decision. Increased the power of the test.
Test the claim about the population mean μ at the level of significance α. Assume the...
Test the claim about the population mean μ at the level of significance α. Assume the population is normally distributed. Write out null and alternative hypotheses, your critical t-score and your t-test statistic. Decide whether you would reject or fail to reject your null hypothesis. Claim μ ≥ 13.9 α = 0.05 Sample statistics: x̅ = 13, s = 1.3, n = 10 H0: Ha: t0: t-test statistic: Decision:
Test the claim about the population mean μ at the level of significance α. Assume the...
Test the claim about the population mean μ at the level of significance α. Assume the population is normally distributed. Write out null and alternative hypotheses, your critical z-score and your z-test statistic. Decide whether you would reject or fail to reject your null hypothesis. Claim: μ > 28; α = 0.05, σ = 1.2 Sample statistics: x̅ = 28.3, n = 50 H0: Ha: Critical z-score: Z test statistic: Decision: