Journal article
Pedagogy of chi-square goodness of fit test for continuous distributions
Computer applications in engineering education, v 27(3), pp 679-689
01 May 2019
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Chi-square goodness of fit testing to examine whether or not it is reasonable to assume that a random sample of the data comes from a specific probability density was one of the topics covered in an undergraduate engineering probability course. In the absence of details on this topic in engineering probability books, a Matlab((R)) demo was created to facilitate the link between theory and practice. The step-by-step procedure to determine the closest fit among a number of continuous densities has been demonstrated involving binning (fixed width and fixed population), parameter estimation, and computation of the test statistic, degrees of freedom and the P values. The cautionary aspects of the test regarding the variability in test results have been illustrated by choosing a smaller size data through permutation. The pedagogical aspects of procedure demonstrated suggest that it may be used to fill the gaps in textbooks devoted to probability and statistics.
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Details
- Title
- Pedagogy of chi-square goodness of fit test for continuous distributions
- Creators
- P. Mohana Shankar - Drexel University
- Publication Details
- Computer applications in engineering education, v 27(3), pp 679-689
- Publisher
- Wiley
- Number of pages
- 11
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000472002200012
- Scopus ID
- 2-s2.0-85062613374
- Other Identifier
- 991019167933304721
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- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Education, Scientific Disciplines
- Engineering, Multidisciplinary