Pedagogy of chi‐square goodness of fit test for continuous distributions
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...
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| Veröffentlicht in: | Computer applications in engineering education 2019-05, Vol.27 (3), p.679-689 |
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| creator | Shankar, P. Mohana |
| description | 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® 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. |
| doi_str_mv | 10.1002/cae.22107 |
| format | Article |
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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.</description><subject>Chi-square test</subject><subject>Goodness of fit</subject><subject>goodness of fit test</subject><subject>Matlab</subject><subject>Parameter estimation</subject><subject>pedagogy</subject><subject>Permutations</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>test statistic</subject><subject>Textbooks</subject><subject>undergraduate engineering statistics</subject><issn>1061-3773</issn><issn>1099-0542</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kL1OwzAQgC0EEqUw8AaWmBjSnu0kjseqKgVUCQaYLdc_xVWJWzsR6sYj8Iw8CQlhZbqT7ru_D6FrAhMCQKda2QmlBPgJGhEQIoMip6d9XpKMcc7O0UVKWwAQJRMj9PhsjdqEzREHh_Wb__78SodWRYs3IZjaptQXnG9wY1ODXYhYh7rxdRvahI1PTfTrtvGhTpfozKldsld_cYxe7xYv8_ts9bR8mM9WmaaC84wSosAaYzhZM-A8zznTznKWO-1AVIVmLBdABRCmwEBZUFdWhFRVTpyyBRujm2HuPoZD210lt6GNdbdSUkqL7msGPXU7UDqGlKJ1ch_9u4pHSUD2qmSnSv6q6tjpwH74nT3-D8r5bDF0_AAP-2of</recordid><startdate>201905</startdate><enddate>201905</enddate><creator>Shankar, P. Mohana</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-9719-9700</orcidid></search><sort><creationdate>201905</creationdate><title>Pedagogy of chi‐square goodness of fit test for continuous distributions</title><author>Shankar, P. Mohana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2977-211a0eddd71b30774473cfe734fcf0985c3349029013a0d0652f68118841fae53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Chi-square test</topic><topic>Goodness of fit</topic><topic>goodness of fit test</topic><topic>Matlab</topic><topic>Parameter estimation</topic><topic>pedagogy</topic><topic>Permutations</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><topic>test statistic</topic><topic>Textbooks</topic><topic>undergraduate engineering statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shankar, P. Mohana</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computer applications in engineering education</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shankar, P. Mohana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pedagogy of chi‐square goodness of fit test for continuous distributions</atitle><jtitle>Computer applications in engineering education</jtitle><date>2019-05</date><risdate>2019</risdate><volume>27</volume><issue>3</issue><spage>679</spage><epage>689</epage><pages>679-689</pages><issn>1061-3773</issn><eissn>1099-0542</eissn><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® 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
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| subjects | Chi-square test Goodness of fit goodness of fit test Matlab Parameter estimation pedagogy Permutations Statistical analysis Statistical tests test statistic Textbooks undergraduate engineering statistics |
| title | Pedagogy of chi‐square goodness of fit test for continuous distributions |
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