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Nonparametric statistical methods

Course Description: Concept of Nonparametric Statistics. - Calculation of the density function and cumulative distribution function. - Statistical tests based on the binomial distribution (binomial test and proportion estimation, spring test and spring estimation, finding tolerance limits with some applications). - Contingency tables and paired tables in (median tests, measures of independence, chi-squared tests, Cochran's test for related observations). - Some nonparametric methods based on ranks (two independent samples, several independent samples, test of equality of variances, rank correlation coefficient test, related data, randomness tests). - Kolmogorov-Smirnov tests (Kolmogorov-Smirnov goodness-of-fit test, goodness-of-fit for a family of distributions).
Credit hours: 3
Prerequisites: 321 STAT
Objectives of the course :

This course aims to introduce the student to the concepts of non-parametric statistics and some of its specific tests.

Course outputs :

Acquiring knowledge by learning basic concepts and tests related to non-parametric statistics and its uses. Enhancing the ability to use non-parametric statistics concepts in identifying and approximating non-parametric statistical population distributions. Acquiring cognitive skills through thinking to solve some life problems. Increasing the ability to pursue advanced studies in statistics when needed.

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  • Last updated: 2026-06-03

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