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Non-parametric Statistics

This quiz covers the fundamental concepts and methods of non-parametric statistics, a branch of statistics that makes no assumptions about the underlying distribution of data.

15 Questions Published
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Questions

Question 1 Multiple Choice (Single Answer)

Which of the following is a non-parametric statistical test?

  1. t-test
  2. ANOVA
  3. Chi-square test
  4. Linear regression
Question 2 Multiple Choice (Single Answer)

What is the main advantage of using non-parametric tests?

  1. They are more powerful than parametric tests.
  2. They are less sensitive to outliers.
  3. They do not require the data to be normally distributed.
  4. They are easier to interpret.
Question 3 Multiple Choice (Single Answer)

Which of the following is a rank-based non-parametric test?

  1. Mann-Whitney U test
  2. Kruskal-Wallis test
  3. Wilcoxon signed-rank test
  4. All of the above
Question 4 Multiple Choice (Single Answer)

What is the null hypothesis in a non-parametric test?

  1. The data is normally distributed.
  2. The medians of the two groups are equal.
  3. The two groups are independent.
  4. The data is randomly distributed.
Question 5 Multiple Choice (Single Answer)

Which of the following is a distribution-free test?

  1. t-test
  2. ANOVA
  3. Chi-square test
  4. F-test
Question 6 Multiple Choice (Single Answer)

What is the p-value in a non-parametric test?

  1. The probability of obtaining the observed results, assuming the null hypothesis is true.
  2. The probability of obtaining the observed results, assuming the alternative hypothesis is true.
  3. The probability of obtaining the observed results, assuming the data is normally distributed.
  4. The probability of obtaining the observed results, assuming the data is randomly distributed.
Question 7 Multiple Choice (Single Answer)

What is the critical value in a non-parametric test?

  1. The value of the test statistic that corresponds to the desired level of significance.
  2. The value of the test statistic that corresponds to the null hypothesis.
  3. The value of the test statistic that corresponds to the alternative hypothesis.
  4. The value of the test statistic that corresponds to the p-value.
Question 8 Multiple Choice (Single Answer)

What is the difference between a parametric and a non-parametric test?

  1. Parametric tests make assumptions about the underlying distribution of the data, while non-parametric tests do not.
  2. Parametric tests are more powerful than non-parametric tests.
  3. Non-parametric tests are easier to interpret than parametric tests.
  4. All of the above
Question 9 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric measure of central tendency?

  1. Mean
  2. Median
  3. Mode
  4. Standard deviation
Question 10 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric measure of variability?

  1. Range
  2. Variance
  3. Standard deviation
  4. Coefficient of variation
Question 11 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric test for comparing two independent groups?

  1. t-test
  2. ANOVA
  3. Mann-Whitney U test
  4. Kruskal-Wallis test
Question 12 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric test for comparing two related groups?

  1. t-test
  2. ANOVA
  3. Wilcoxon signed-rank test
  4. Friedman test
Question 13 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric test for comparing three or more independent groups?

  1. t-test
  2. ANOVA
  3. Kruskal-Wallis test
  4. Friedman test
Question 14 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric test for comparing three or more related groups?

  1. t-test
  2. ANOVA
  3. Friedman test
  4. Kendall's coefficient of concordance
Question 15 Multiple Choice (Single Answer)

Which of the following is an example of a non-parametric test for testing the independence of two categorical variables?

  1. t-test
  2. ANOVA
  3. Chi-square test
  4. Fisher's exact test
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