Question 1 (1 point) Question 1: Which of the following statements is not true o
ID: 3059467 • Letter: Q
Question
Question 1 (1 point)
Question 1: Which of the following statements is not true of parametric statistics?
Question 1 options:
They are inferential tests.
They assume certain characteristics of population parameters.
They assume normality of the population.
They are distribution-free.
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Question 2 (1 point)
Question 2: Assume you are conducting a study and find that the data violate all the assumptions of the statistic you had planned to conduct, what are your alternatives?
Question 2 options:
Conduct the statistical test since there will be no evidence of the error.
Run the study again and hope the data are better.
Conduct a nonparametric statistical test.
Change the research question.
Save
Question 3 (1 point)
Question 3: Under what circumstances would you use a non- parametric test?
Question 3 options:
In a pilot study.
When your data does not meet the assumptions for a parametric test.
When you think your sample size is too big.
When you do not really understand a parametric test.
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Question 4 (1 point)
Question 4: Nonparametric tests are just as powerful as their parametric counterparts.
Question 4 options:
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Question 5 (1 point)
Question 5: The Mann-Whitney U test is the nonparametric counterpart for which parametric test?
Question 5 options:
One-sample t-test.
Two-dependent sample t-test
Two-independent sample t-test.
Kruskal-Wallis Test
Save
They are inferential tests.
They assume certain characteristics of population parameters.
They assume normality of the population.
They are distribution-free.
Explanation / Answer
Question 1 (1 point)
Question 1: Which of the following statements is not true of parametric statistics?
Question 1 options:
They are inferential tests.
They assume certain characteristics of population parameters.
They assume normality of the population.
They are distribution-free.
Save
Question 2 (1 point)
Question 2: Assume you are conducting a study and find that the data violate all the assumptions of the statistic you had planned to conduct, what are your alternatives?
Question 2 options:
Conduct the statistical test since there will be no evidence of the error.
Run the study again and hope the data are better.
Conduct a nonparametric statistical test.
Change the research question.
Save
Question 3 (1 point)
Question 3: Under what circumstances would you use a non- parametric test?
Question 3 options:
In a pilot study.
When your data does not meet the assumptions for a parametric test.
When you think your sample size is too big.
When you do not really understand a parametric test.
Save
Question 4 (1 point)
Question 4: Nonparametric tests are just as powerful as their parametric counterparts.
Question 4 options:
Save
Question 5 (1 point)
Question 5: The Mann-Whitney U test is the nonparametric counterpart for which parametric test?
Question 5 options:
One-sample t-test.
Two-dependent sample t-test
Two-independent sample t-test.
Kruskal-Wallis Test
Save
They are inferential tests.
They assume certain characteristics of population parameters.
They assume normality of the population.
They are distribution-free.