Non-Parametric Tests

Important MCQs Nonparametric Quiz 1

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The post is about MCQs nonparametric quiz. There are 22 multiple-choice questions covering different nonparametric tests such as Wilcoxon rank sum test, Spearman’s Rank Correlation test, Mann-Whitney U test, Sign test, Runs Test, Kruskal Wallis test, and Chi-Square goodness of fit test. Let us start with the MCQs nonparametric Quiz.

MCQs about non-Parametric Statistics

1. The Spearman rank-correlation test requires that the

 
 
 
 

2. Which of the following tests must be two-sided?

 
 
 
 

3. The Mann-Whitney U test is preferred to a t-test when

 
 
 
 

4. When using the Sign test, if two scores are tied, then we

 
 
 
 

5. To perform a run test for randomness the data must be

 
 
 
 

6. In testing for the difference between two populations, it is possible to use

 
 
 
 

7. The Wilcoxon rank-sum test compares

 
 
 
 

8. When testing for randomness, we can use

 
 
 
 

9. The sign test is

 
 
 
 

10. The sign test assumes that the samples are

 
 
 
 

11. Which of the following tests is most likely assessing the null hypothesis of “the number of violations per apartment in the population of all city apartments is binomially distributed with a probability of success in any one trial of $P=0.4”

 
 
 
 

12. If a Chi-square goodness of fit test has 6 categories and an N=30, then the correct number of degrees of freedom is

 
 
 
 

13. Comparing the times-to-failure of radar transponders made by firms A, B, and C, based on an airline’s sample experience with the three types of instruments, one may well call for:

 
 
 
 

14. Compare to parametric methods, the nonparametric methods are

 
 
 
 

15. The nonparametric equivalent of an unpaired samples t-test is

 
 
 
 

16. The Runs test results in rejecting the null hypothesis of randomness when:

 
 
 
 

17. In a Wilcoxon rank-sum test

 
 
 
 

18. The Wilcoxon rank-sum test can be

 
 
 
 

19. Three brands of coffee are rated for taste on a scale of 1 to 10. Six persons are asked to rate each brand so that there is a total of 18 observations. The appropriate test to determine if three brands taste equally good is

 
 
 
 

20. The Wilcoxon signed rank is used

 
 
 
 

21. In the Kruskal-Wallis test of $k$ samples, the appropriate number of degrees of freedom is

 
 
 
 

22. Which of the following test use rank sums?

 
 
 
 

Online MCQs Nonparametric Quiz with Answers

MCQs nonparametric test
  • The Wilcoxon rank-sum test can be
  • The Wilcoxon rank-sum test compares
  • The Wilcoxon signed rank is used
  • Which of the following test use rank sums?
  • Which of the following tests must be two-sided?
  • In testing for the difference between two populations, it is possible to use
  • In a Wilcoxon rank-sum test
  • The Spearman rank-correlation test requires that the
  • The sign test is
  • The nonparametric equivalent of an unpaired samples t-test is
  • The Mann-Whitney U test is preferred to a t-test when
  • When using the Sign test, if two scores are tied, then we
  • The sign test assumes that the samples are
  • When testing for randomness, we can use
  • The Runs test results in rejecting the null hypothesis of randomness when:
  • To perform a run test for randomness the data must be
  • Three brands of coffee are rated for taste on a scale of 1 to 10. Six persons are asked to rate each brand so that there is a total of 18 observations. The appropriate test to determine if three brands taste equally good is
  • If a Chi-square goodness of fit test has 6 categories and an N=30, then the correct number of degrees of freedom is
  • Comparing the times-to-failure of radar transponders made by firms A, B, and C, based on an airline’s sample experience with the three types of instruments, one may well call for:
  • Which of the following tests is most likely assessing the null hypothesis of “the number of violations per apartment in the population of all city apartments is binomially distributed with a probability of success in any one trial of $P=0.4$
  • In the Kruskal-Wallis test of $k$ samples, the appropriate number of degrees of freedom is
  • Compare to parametric methods, the nonparametric methods are
MCQs nonparametric Statistics Quiz with answers

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Important Chi-Square Test MCQs with Answers 4

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The post is about the Chi-Square Test MCQS with Answers. The Chi-square test is used to find the association between attributes. Let us start with the Chi-Square Test MCQs with Answers.

Please go to Important Chi-Square Test MCQs with Answers 4 to view the test

The relationship/ Dependency between the attributes is called association and the measure of degrees of relationship between attributes is called the coefficient of association. The Chi-Square Statistic is used to test the association between the attributes. The Chi-Square Association is defined as

$$\chi^2 = \sum \frac{(of_i – ef_i)^2}{ef_i}\sim \chi^2_{v}$$

where $v$$ denotes the degrees of freedom.

The Chi-Square tests:

  • are appropriate for categorical data, not continuous data (like height or weight).
  • The data needs to be from a random sample and have sufficient sample size for the test to be reliable.
  • The test results in a chi-square statistic and a p-value.

Chi-Square Test MCQs with Answers

  • A characteristic which cannot be measured numerically is called
  • Which of the following is not an example of an attribute
  • The eye colour of students in a girl’s college is an example of
  • Religions of the people of a country is
  • The degree of relationship between two attributes is called
  • In a contingency table with $r$ rows and $c$ columns, the degree of freedom is
  • The $\chi^2$ distribution is
  • If $\chi^2_{calculated}$ is greater than the critical region, then the attributes are
  • In a $3 \times 3$ contingency table, the degrees of freedom is
  • The Spearman’s coefficient of rank correlation always lies between
  • The Yule’s coefficient of association lies between
  • If $(AB) < \frac{(A)(B)}{n}$ then the two attributes $A$ and $B$ are said to be
  • If $(AB) = \frac{(A)(B)}{n}$ the attributes $A$ and $B$ are said to be
  • The coefficient of contingency is measured by
  • If $\chi^2_{calculated} = 0$ then
  • $(\alpha \beta)$ is the frequency of the class of the order
  • If $A$ and $B$ are independent attributes then the coefficient of associate is
  • The value of $\chi^2$ is always
  • In a Chi-Square test of independence, no expected frequencies should be
  • The two attributes are said to be ———–, if for every cell of the contingency table, the observed frequency $O_{ij}$ is equal to the expected frequency $e_{ij}$
Chi-Square Test MCQs with Answers

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Easy MCQs Non-Parametric Methods

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Most of the MCQs on this page covered Estimate and Estimation, Testing of Hypothesis when the assumption of population parameters are unknown, that is Non-Parametric Methods, etc.

MCQs Non-Parametric Methods Quizzes List

MCQS Non-Parametric Methods- 6MCQS Non-Parametric Tests- 5MCQS Non-Parametric Tests- 4
MCQS Non-Parametric Tests- 3MCQS Non-Parametric Tests – 2MCQS Non-Parametric Tests – 1
MCQs Non-Parametric Methods

The relationship/ Dependency between the attributes is called association and the measure of degrees of relationship between the attributes is called the coefficient of association. The Chi-Square Statistic is used to test the association between the attributes. The Chi-Square Association is defined as

$$\chi^2 = \sum \frac{(of_i – ef_i)^2}{ef_i}\sim \chi^2_{v},$$

where $v$ denotes the degrees of freedom.

https://itfeature.com Hypothesis Testing Parametric and Non Parametric Tests

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Wilcoxon Signed Rank Test Made Easy

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The Wilcoxon Signed Rank test assumes that the population of interest is both continuous and symmetric (not necessarily normal). Since the mean and median are the same (for symmetrical distribution), the hypothesis tests on the median are the same as the hypothesis test on the mean.

The Wilcoxon test is performed by ranking the non-zero deviations in order of increasing magnitude (that is, the smallest non-zero deviation has a rank of 1 and the largest deviation has a rank of $n$). The ranks of the deviations with positive and negative values are summed.

These sums are used to determine whether or not the deviations are significantly different from zero. Wilcoxon Signed Rank Test is an alternative to the Paired Sample t-test.

One-Tailed Test

$H_0: \mu = \mu_0\quad $ vs $\quad H_1: \mu < \mu_0$

Test Statistics: $T^-$: an absolute value of the sum of the negative ranks

Two-tailed Test

$H_0: \mu = \mu_0 \quad$ vs $\quad H_1:\mu \ne \mu_0$

Test Statistics: $min(T^+, T^-)$

Wilcoxon Signed Ranked Test

Because the underlying population is assumed to be continuous, ties are theoretically impossible, however, in practice ties can exist, especially if the data has only a couple of significant digits.

Two or more deviations having the same magnitude are all given the same average rank. The deviations of zero are theoretically impossible but practically possible. Any deviations of exactly zero are simply thrown out and the value of $n$ is reduced accordingly.

Single Sample Wilcoxon Signed Rank Test

Wilcoxon Signed Rank Test

The Wilcoxon Signed Rank Test is important for researchers as it fills a critical gap in statistical analysis.

  • Non-normal data: Most of the statistical tests, like the dependent samples t-test, assume that the data follows a normal distribution (bell curve). The Wilcoxon Signed Rank Test supersede the assumption of normality, making it ideal for analyzing data that is skewed, ranked, or ordinal (like survey responses on a Likert scale Questions).
  • Robust against outliers: Outliers (very large or small observations in the data) can significantly skew the results of some statistical tests. The Wilcoxon Signed Rank Test focuses on the ranks of the differences, making it less sensitive to extreme values (outliers) in the data compared to tests that rely on raw numbers.
  • Focuses on changes within subjects: The Wilcoxon Signed Rank Test is designed for paired data (dependent samples), to look at the same subjects before and after situation (like a treatment) or under two different conditions.

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