Computation of distribution functions and percentile points for popular statistic tests
Call Number: AIT RSPR no.IM-04-02 Material type:
SeriesSeries: Asian Institute of Technology. Research studies project report ; no. IM-04-02Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2004Description: 51 pSubject(s): Online resources: Dissertation note: Research report (M.Sc.) - Asian Institute of Technology, 2004 Summary: The purpose of this research is to compute and approximate the distribution functions and/or percentile points for some imp01iant distributions, such as normal, gamma, chi-square and Kolmogorov-Smimov. The study also applied the tests based on these distributions to analyze the scores of a number of subjects taught at Tay Nguyen University in Vietnam. It was found that All the computation methods described can provide accurate values of the distribution functions and percentile points of the considered distributions. In a number of cases, the distribution functions and percentile points can also be represented satisfactorily by polynomial curves or surfaces. Although the mean of the scores for a subject can vary from year to year in a two-sample test, the scores over the entire period of four years appear to belong to the same distribution for four out of five subjects. With the computation methods and the approximate formulas provided, one can readily use these in other applications.
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A research study submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Advanced Technologies
Research report (M.Sc.) - Asian Institute of Technology, 2004
The purpose of this research is to compute and approximate the distribution functions and/or percentile points for some imp01iant distributions, such as normal, gamma, chi-square and Kolmogorov-Smimov. The study also applied the tests based on these distributions to analyze the scores of a number of subjects taught at Tay Nguyen University in Vietnam. It was found that All the computation methods described can provide accurate values of the distribution functions and percentile points of the considered distributions. In a number of cases, the distribution functions and percentile points can also be represented satisfactorily by polynomial curves or surfaces. Although the mean of the scores for a subject can vary from year to year in a two-sample test, the scores over the entire period of four years appear to belong to the same distribution for four out of five subjects. With the computation methods and the approximate formulas provided, one can readily use these in other applications.
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