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Which of the following is a true statement about hypothesis
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Which of the following is a true statement about hypothesis testing? (Points: 1)
You conduct hypothesis testing to prove your null hypothesis.
You conduct hypothesis testing to prove your alternative hypothesis.
You conduct hypothesis testing to eliminate the effect of chance on your solution.
You conduct hypothesis testing to test the significance of a perceived relationship between variables.
2. Which of the following is not a true statement about a null hypothesis? (Points: 1)
It is the hypothesis you are trying to prove or disprove.
It is the hypothesis you are testing.
It is a statement of no association between variables or difference between groups.
It is related to the alternative hypothesis.
3. Which of the following is true of the statement: The men in this sample are taller than the women? (Points: 1)
It is a directional null hypothesis.
It is a directional alternative hypothesis.
It is a twotailed alternative hypothesis.
It is a onetailed null hypothesis.
4. Which is the correct null hypothesis based on this statement: People with diabetes have higher systolic blood pressure than people without diabetes? (Points: 1)
People with diabetes have lower systolic blood pressure than people without diabetes.
People with diabetes have equal systolic blood pressure when compared to people without diabetes.
People with diabetes have a systolic blood pressure equal to or lower than people without diabetes.
None of these are a null hypothesis.
5. Which of the following is an example of a Type 1 error? (Points: 1)
Rejecting a false null hypothesis.
Rejecting a true null hypothesis.
Failing to reject a false null hypothesis.
Failing to reject a true null hypothesis.
6. Which of the following is an example of a Type 2 error? (include on all quizzes) (Points: 1)
Rejecting a false null hypothesis.
Rejecting a true null hypothesis.
Failing to reject a false null hypothesis.
Failing to reject a true null hypothesis.
7. Which of the following is a true statement about Power? (Points: 1)
It is the additive inverse of a Type 2 error.
It is the opposite of a Type 2 error.
It is the additive inverse of a Type 1 error.
It is the opposite of a Type 1 error.
8. Which of the following statements about Type 1 and Type 2 error is false? (Points: 1)
They are both a form of chance error.
They are both represented using Greek letters.
They are both a form of systematic error.
Ideally you should try to keep both as low as possible in your study.
9. Which of the following is not true about Power? (Points: 1)
A study conducted with insufficient Power has a high chance of a Type 2 error.
Whenever you read of a study where they were unable to reject the null hypothesis you should check whether it had enough Power.
It is related to the Type 1 error rate you set for your study.
If sample size is constant, if you prespecify a higher type I error, the statistical power will increase.
10. Which of the following is the correct definition of Power? (Points: 1)
It is the likelihood of an investigator to reject a null hypothesis that is false and should be rejected.
It is the likelihood of an investigator to fail to reject a null hypothesis that is false and should be rejected.
It is the likelihood of an investigator to reject a null hypothesis that is true and should not be rejected.
It is the likelihood of an investigator to fail to reject a null hypothesis that is true and should not be rejected.
11. Given a Type 2 error rate of .15, what is the Power? (Points: 1)
15%
1.15
85%
Unable to calculate given the information.
12. Given a Type 2 error rate of .10, what is the Power? (Points: 1)
10%
90%
1.10
Unable to calculate given the information.
13. Which of the following is not true about Sample Size calculations? (Points: 1)
It depends on the type of statistical test you plan to use.
It can be calculated using software.
Some of the values used in calculating it are estimates.
It can be computed after performing the test to see if you had sufficient sample size.
14. Which of the following is true about sample size? (Points: 1)
The sample size you calculate will always be sufficient to conduct your statistical tests.
Things like unanswered questions and dropouts can reduce the available sample size.
The size of the effect you are trying to observe, whether a difference in means or an association between variables is not important when computing sample size.
A sample size of 100 is always sufficient.
15. Which is a reason for keeping your sample size as small as possible? (Points: 1)
Time required to analyze the data
Cost of analyzing the data
Cost of collecting the data
Controlling for Chance error
16. Which is not a reason for making your sample size as large as possible? (Points: 1)
Reducing Type 1 error
Reducing Systematic error
Reducing Chance error
Reducing Type 2 error
17. What does the Z1  α/2 represent in a sample size calculation? (Points: 1)
The Z value for the expected difference in means.
The Z value for the Type 2 error rate.
The Z value for the Type 1 error rate.
The Z value for the expected variance.
18. Which of the following parts of a sample size calculation are usually educated guesses? (Points: 1)
Z1  α/2
ES
Z1  β
None of the above
19. What happens to the following sample size calculation if you increase the value for ES: n = ((1.96 + .84)/2)2? (Points: 1)
The sample size goes down.
The sample size stays the same.
The sample size goes up.
Impossible to say given the information.
20. What happens to the following sample size calculation if you increase the value for Z1  β: n = ((1.96 + .84)/2)2? (Points: 1)
The sample size goes down.
The sample size stays the same.
The sample size goes up.
Impossible to say given the information.
Submitted:
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