This paper proposes a non parametric method for two factor data analysis with unequal cell frequencies and interaction. Chi-square test statistic was developed for testing the null hypothesis of no treatment effect and interaction between factor A and factor B. The proposed methods are illustrated with some data and compared with the usual unweighted mean method. The result showed that the proposed method is more powerful than the method of unweighted mean.
| Published in | Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 6) |
| DOI | 10.11648/j.sjams.20150306.18 |
| Page(s) | 288-292 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Cell Frequency, Interaction, Chi-square, Unweighted Mean, Ranking, Tied Observation
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APA Style
Chinwendu Alice Uzuke, Ikewelugo Cyprian Anene Oyeka, Happiness Onyebuchi Obiora-Ilouno. (2015). Two Factor Data Analysis with Unequal Cell Frequencies and Interaction. Science Journal of Applied Mathematics and Statistics, 3(6), 288-292. https://doi.org/10.11648/j.sjams.20150306.18
ACS Style
Chinwendu Alice Uzuke; Ikewelugo Cyprian Anene Oyeka; Happiness Onyebuchi Obiora-Ilouno. Two Factor Data Analysis with Unequal Cell Frequencies and Interaction. Sci. J. Appl. Math. Stat. 2015, 3(6), 288-292. doi: 10.11648/j.sjams.20150306.18
AMA Style
Chinwendu Alice Uzuke, Ikewelugo Cyprian Anene Oyeka, Happiness Onyebuchi Obiora-Ilouno. Two Factor Data Analysis with Unequal Cell Frequencies and Interaction. Sci J Appl Math Stat. 2015;3(6):288-292. doi: 10.11648/j.sjams.20150306.18
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Download@article{10.11648/j.sjams.20150306.18,
author = {Chinwendu Alice Uzuke and Ikewelugo Cyprian Anene Oyeka and Happiness Onyebuchi Obiora-Ilouno},
title = {Two Factor Data Analysis with Unequal Cell Frequencies and Interaction},
journal = {Science Journal of Applied Mathematics and Statistics},
volume = {3},
number = {6},
pages = {288-292},
doi = {10.11648/j.sjams.20150306.18},
url = {https://doi.org/10.11648/j.sjams.20150306.18},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150306.18},
abstract = {This paper proposes a non parametric method for two factor data analysis with unequal cell frequencies and interaction. Chi-square test statistic was developed for testing the null hypothesis of no treatment effect and interaction between factor A and factor B. The proposed methods are illustrated with some data and compared with the usual unweighted mean method. The result showed that the proposed method is more powerful than the method of unweighted mean.},
year = {2015}
}
TY - JOUR T1 - Two Factor Data Analysis with Unequal Cell Frequencies and Interaction AU - Chinwendu Alice Uzuke AU - Ikewelugo Cyprian Anene Oyeka AU - Happiness Onyebuchi Obiora-Ilouno Y1 - 2015/12/25 PY - 2015 N1 - https://doi.org/10.11648/j.sjams.20150306.18 DO - 10.11648/j.sjams.20150306.18 T2 - Science Journal of Applied Mathematics and Statistics JF - Science Journal of Applied Mathematics and Statistics JO - Science Journal of Applied Mathematics and Statistics SP - 288 EP - 292 PB - Science Publishing Group SN - 2376-9513 UR - https://doi.org/10.11648/j.sjams.20150306.18 AB - This paper proposes a non parametric method for two factor data analysis with unequal cell frequencies and interaction. Chi-square test statistic was developed for testing the null hypothesis of no treatment effect and interaction between factor A and factor B. The proposed methods are illustrated with some data and compared with the usual unweighted mean method. The result showed that the proposed method is more powerful than the method of unweighted mean. VL - 3 IS - 6 ER -
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