Recently, Nigeria focused on Agriculture as a way to diversify her economy. Crop production, which is a proxy to measure agricultural output is considered very important. So, controlling crop production (output) among states in Nigeria is very key. In this study, the generalized regression control chart was used rather than the conventional control chart. The conventional control chart does not put into consideration factor(s) that affect crop production. The generalized regression control chart considers the factor (independent variable) that affect crop production (dependent variable). The normal distribution is a special case of the generalized regression control chart. The possibility of using Weibull regression and other non-normal models were considered. In this research, Gaussian distribution was used as the underlying distribution because it fitted the crop production data. The cost of seed/seedling was selected from a set of independent variables, because it is most significant among other independent variables. The data were collected from secondary sources, precisely National Bureau of Statistics (NBS). All the 36 states in Nigeria, including the Federal Capital Territory (FCT) were involved in the study. The result of the generalized regression control chart showed that crop production is not in control in Nigeria, which was traced to assignable cause of variation in FCT, Abuja. This implied that FCT, Abuja produced below the lower control limit of crop production, despite the relative cost of seed/seedlings.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 9, Issue 4) |
| DOI | 10.11648/j.ajtas.20200904.12 |
| Page(s) | 90-100 |
| 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), 2020. Published by Science Publishing Group |
Conventional Control Chart, Crop Production, Exponential Family, Gaussian Regression Model, Generalized Regression Control Chart
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APA Style
Olatunji Taofik Arowolo, Matthew Iwada Ekum. (2020). Generalized Regression Control Chart for Monitoring Crop Production. American Journal of Theoretical and Applied Statistics, 9(4), 90-100. https://doi.org/10.11648/j.ajtas.20200904.12
ACS Style
Olatunji Taofik Arowolo; Matthew Iwada Ekum. Generalized Regression Control Chart for Monitoring Crop Production. Am. J. Theor. Appl. Stat. 2020, 9(4), 90-100. doi: 10.11648/j.ajtas.20200904.12
AMA Style
Olatunji Taofik Arowolo, Matthew Iwada Ekum. Generalized Regression Control Chart for Monitoring Crop Production. Am J Theor Appl Stat. 2020;9(4):90-100. doi: 10.11648/j.ajtas.20200904.12
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Download@article{10.11648/j.ajtas.20200904.12,
author = {Olatunji Taofik Arowolo and Matthew Iwada Ekum},
title = {Generalized Regression Control Chart for Monitoring Crop Production},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {9},
number = {4},
pages = {90-100},
doi = {10.11648/j.ajtas.20200904.12},
url = {https://doi.org/10.11648/j.ajtas.20200904.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20200904.12},
abstract = {Recently, Nigeria focused on Agriculture as a way to diversify her economy. Crop production, which is a proxy to measure agricultural output is considered very important. So, controlling crop production (output) among states in Nigeria is very key. In this study, the generalized regression control chart was used rather than the conventional control chart. The conventional control chart does not put into consideration factor(s) that affect crop production. The generalized regression control chart considers the factor (independent variable) that affect crop production (dependent variable). The normal distribution is a special case of the generalized regression control chart. The possibility of using Weibull regression and other non-normal models were considered. In this research, Gaussian distribution was used as the underlying distribution because it fitted the crop production data. The cost of seed/seedling was selected from a set of independent variables, because it is most significant among other independent variables. The data were collected from secondary sources, precisely National Bureau of Statistics (NBS). All the 36 states in Nigeria, including the Federal Capital Territory (FCT) were involved in the study. The result of the generalized regression control chart showed that crop production is not in control in Nigeria, which was traced to assignable cause of variation in FCT, Abuja. This implied that FCT, Abuja produced below the lower control limit of crop production, despite the relative cost of seed/seedlings.},
year = {2020}
}
TY - JOUR T1 - Generalized Regression Control Chart for Monitoring Crop Production AU - Olatunji Taofik Arowolo AU - Matthew Iwada Ekum Y1 - 2020/05/28 PY - 2020 N1 - https://doi.org/10.11648/j.ajtas.20200904.12 DO - 10.11648/j.ajtas.20200904.12 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 90 EP - 100 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20200904.12 AB - Recently, Nigeria focused on Agriculture as a way to diversify her economy. Crop production, which is a proxy to measure agricultural output is considered very important. So, controlling crop production (output) among states in Nigeria is very key. In this study, the generalized regression control chart was used rather than the conventional control chart. The conventional control chart does not put into consideration factor(s) that affect crop production. The generalized regression control chart considers the factor (independent variable) that affect crop production (dependent variable). The normal distribution is a special case of the generalized regression control chart. The possibility of using Weibull regression and other non-normal models were considered. In this research, Gaussian distribution was used as the underlying distribution because it fitted the crop production data. The cost of seed/seedling was selected from a set of independent variables, because it is most significant among other independent variables. The data were collected from secondary sources, precisely National Bureau of Statistics (NBS). All the 36 states in Nigeria, including the Federal Capital Territory (FCT) were involved in the study. The result of the generalized regression control chart showed that crop production is not in control in Nigeria, which was traced to assignable cause of variation in FCT, Abuja. This implied that FCT, Abuja produced below the lower control limit of crop production, despite the relative cost of seed/seedlings. VL - 9 IS - 4 ER -
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