nonparametric statistic Sentence Examples

  1. Nonparametric statistics offer a powerful tool for analyzing data without assuming a specific distribution.
  2. The Wilcoxon rank-sum test is a common nonparametric statistic used to compare two independent groups.
  3. The Kruskal-Wallis test is a nonparametric analogue of ANOVA for comparing multiple independent groups.
  4. Nonparametric statistics are often used when the sample size is small or the data distribution is highly skewed.
  5. The Friedman test is a nonparametric statistic used to compare multiple related groups.
  6. Nonparametric statistics provide a more robust alternative to parametric tests when assumptions about the data distribution are questionable.
  7. The Mann-Whitney U test is a nonparametric statistic used to test for differences between two independent groups with ordinal data.
  8. Nonparametric statistics can handle outliers and missing data more effectively than parametric tests.
  9. The Spearman's rank correlation coefficient is a nonparametric measure of association between two variables.
  10. Nonparametric statistics have gained widespread use in fields such as psychology, sociology, and environmental science.

nonparametric statistic Meaning

Wordnet

nonparametric statistic (n)

a statistic computed without knowledge of the form or the parameters of the distribution from which observations are drawn

Synonyms & Antonyms of nonparametric statistic

No Synonyms and anytonyms found

FAQs About the word nonparametric statistic

a statistic computed without knowledge of the form or the parameters of the distribution from which observations are drawn

No synonyms found.

No antonyms found.

Nonparametric statistics offer a powerful tool for analyzing data without assuming a specific distribution.

The Wilcoxon rank-sum test is a common nonparametric statistic used to compare two independent groups.

The Kruskal-Wallis test is a nonparametric analogue of ANOVA for comparing multiple independent groups.

Nonparametric statistics are often used when the sample size is small or the data distribution is highly skewed.