Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)

Oladimeji Olanrewaju Adedipupo; Akomolafe Abayomi Ayodele; Lasisi Taiwo Abideen; Ojo Thompson Olabode; Adesina Oluwaseun Ayobami; Egbedokun Gabriel Olumide

doi:doi:10.11648/j.ijssam.20220703.11

Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)

Oladimeji Olanrewaju Adedipupo, Akomolafe Abayomi Ayodele, Lasisi Taiwo Abideen, Ojo Thompson Olabode, Adesina Oluwaseun Ayobami, Egbedokun Gabriel Olumide

Published in International Journal of Systems Science and Applied Mathematics (Volume 7, Issue 3)

Received: 7 June 2022 Accepted: 29 June 2022 Published: 17 August 2022

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Abstract

Nigeria, a developing nation is experiencing the overwhelming effects of her exponentially ever-increasing population. This paper is aimed at projecting the future population of Nigeria using the exponential and geometric growth models from 1991 and 2006 population censuses of Nigeria. The resultant effects are clearly evident for all stakeholders to see and feel. Researches have been carried out to study, explain and recommend likely solutions to the population growth of Nigeria. The data used in this research paper were extracted from the National Population Commission of Nigeria bulletin which was secondary data. The forecast for Geometric and Exponential models were made using last Nigeria population census 2006 as base population and projection were made from 2012 to 2022 and adopt the Root Mean Square Error (RMSE) to detect which of the methods adopted is better for population projection. RMSE of both geometric and exponential population projections are 1,832,610,950 and 1,930,404,821 respectively. The multiple bar chart was drawn which indicated higher increase in population projection for both geometric and exponential growth models.

Published in	International Journal of Systems Science and Applied Mathematics (Volume 7, Issue 3)
DOI	10.11648/j.ijssam.20220703.11
Page(s)	46-51
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), 2022. Published by Science Publishing Group

Keywords

Population Census, Exponential Model, Geometric Model, Average, Annual Rate, Growth Survey, Sum of Square Error, Projection

References

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[2]	Ajala, O. A. and Olayiwola, A. M. (2013): An Assessment of the Growth of Ile-Ife, Osun State, Nigeria, Using Multi-Temporal Imageries, Journal of Geography and Geology Vol. 5 (2).
[3]	Bewick V, Cheek L, Ball J. Statistics review 14: Logistic regression. Critical Care. 2005; 9 (1).
[4]	Eli HT, Mohammed ID, Amade P. Impact of population growth on economic growth in Nigeria (1980-2010). Journal of Humanities and Social Science. 2015; 20 (4): 115-123.
[5]	Eniayejuni, A. T., Agoyi, M (2011): A Biometrics Approach to Population Census and National Identification in Nigeria: A Prerequisite for Planning and Development, Asian Transactionson Basic & Applied Sciences, Vol. 1 (5).
[6]	Folorunso, O., Akinwale, A., T. Asiribo, O. E. and Adeyemo, T. A. (2010): Population prediction using artificial neural network, African Journal of Mathematics and Computer Science Research Vol. 3 (8), pp. 155-162.
[7]	Gee, Ellen M. (1999): Population Growth Retrieved on 19th January, 2013, fromhttp://www.deathreference.com/Nu-Pu/population- Growth.
[8]	Hosmer D, Lemeshow S. Applied logistic regression. New York: Wiley; 2000.
[9]	Irewole, F., Akeem, A O., Babalola, J. B and Kuranga J. L (2014): Modelling of population projection and symptomatic estimated population in Nigeria. IPASJ International Journal of Management, Vol. 2 (1).
[10]	Nwosu, C., Dike, A. O and Okwara, K. K. (2014): The Effects of Population Growth on Economic Growth in Nigeria. The International Journal of Engineering And Science (IJES), Vol. 3 (11), pp: 07-18.
[11]	Ogunleye OO, Owolabi OA, Mubarak M. Population growth and economic growth in Nigeria: An appraisal. International Journal of Management, Accounting and Economics. 2018; 5 (5): 282-299.
[12]	Olatayo, T. O and Adeboye, N. O (2013): Predicting Population Growth through Births and Deaths Rate in Nigeria, Mathematical Theory and Modeling, Vol. 3 (1).
[13]	Olayiwola, O. M., Lawal. G. O, Amalare, A. A, Agboluaje, S. A, Fantola, J. O, (2015): Modelling Nigeria Population Growth Rate. Journal of Advances In Mathematics Vol. 10 (6).
[14]	Onwuka, E. C (2011): Another Look at the Impact of Nigeria’s Growing Population on the Country’s Development. African Population Studies Vol. 21 (1).
[15]	Oyinloye, M. A. and Fasakin, J. O (2014): Modelling urban growth from medium resolution LANDSAT imageries of Akure, Nigeria. International Journal for Innovation Education and Research Vol. 2 (6).
[16]	United Nations. Department of Economic and Social Affairs, Population Division. World Population Prospects 2019: Highlights. ST/ESA/SER.A/423; 2019. Available: https://population.un.org/wpp/Publications/Files/WPP2019_Highlights.pdf

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APA Style

Oladimeji Olanrewaju Adedipupo, Akomolafe Abayomi Ayodele, Lasisi Taiwo Abideen, Ojo Thompson Olabode, Adesina Oluwaseun Ayobami, et al. (2022). Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). International Journal of Systems Science and Applied Mathematics, 7(3), 46-51. https://doi.org/10.11648/j.ijssam.20220703.11

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ACS Style

Oladimeji Olanrewaju Adedipupo; Akomolafe Abayomi Ayodele; Lasisi Taiwo Abideen; Ojo Thompson Olabode; Adesina Oluwaseun Ayobami, et al. Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). Int. J. Syst. Sci. Appl. Math. 2022, 7(3), 46-51. doi: 10.11648/j.ijssam.20220703.11

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AMA Style

Oladimeji Olanrewaju Adedipupo, Akomolafe Abayomi Ayodele, Lasisi Taiwo Abideen, Ojo Thompson Olabode, Adesina Oluwaseun Ayobami, et al. Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). Int J Syst Sci Appl Math. 2022;7(3):46-51. doi: 10.11648/j.ijssam.20220703.11

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@article{10.11648/j.ijssam.20220703.11,
  author = {Oladimeji Olanrewaju Adedipupo and Akomolafe Abayomi Ayodele and Lasisi Taiwo Abideen and Ojo Thompson Olabode and Adesina Oluwaseun Ayobami and Egbedokun Gabriel Olumide},
  title = {Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {7},
  number = {3},
  pages = {46-51},
  doi = {10.11648/j.ijssam.20220703.11},
  url = {https://doi.org/10.11648/j.ijssam.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20220703.11},
  abstract = {Nigeria, a developing nation is experiencing the overwhelming effects of her exponentially ever-increasing population. This paper is aimed at projecting the future population of Nigeria using the exponential and geometric growth models from 1991 and 2006 population censuses of Nigeria. The resultant effects are clearly evident for all stakeholders to see and feel. Researches have been carried out to study, explain and recommend likely solutions to the population growth of Nigeria. The data used in this research paper were extracted from the National Population Commission of Nigeria bulletin which was secondary data. The forecast for Geometric and Exponential models were made using last Nigeria population census 2006 as base population and projection were made from 2012 to 2022 and adopt the Root Mean Square Error (RMSE) to detect which of the methods adopted is better for population projection. RMSE of both geometric and exponential population projections are 1,832,610,950 and 1,930,404,821 respectively. The multiple bar chart was drawn which indicated higher increase in population projection for both geometric and exponential growth models.},
 year = {2022}
}

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TY  - JOUR
T1  - Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)
AU  - Oladimeji Olanrewaju Adedipupo
AU  - Akomolafe Abayomi Ayodele
AU  - Lasisi Taiwo Abideen
AU  - Ojo Thompson Olabode
AU  - Adesina Oluwaseun Ayobami
AU  - Egbedokun Gabriel Olumide
Y1  - 2022/08/17
PY  - 2022
N1  - https://doi.org/10.11648/j.ijssam.20220703.11
DO  - 10.11648/j.ijssam.20220703.11
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 46
EP  - 51
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20220703.11
AB  - Nigeria, a developing nation is experiencing the overwhelming effects of her exponentially ever-increasing population. This paper is aimed at projecting the future population of Nigeria using the exponential and geometric growth models from 1991 and 2006 population censuses of Nigeria. The resultant effects are clearly evident for all stakeholders to see and feel. Researches have been carried out to study, explain and recommend likely solutions to the population growth of Nigeria. The data used in this research paper were extracted from the National Population Commission of Nigeria bulletin which was secondary data. The forecast for Geometric and Exponential models were made using last Nigeria population census 2006 as base population and projection were made from 2012 to 2022 and adopt the Root Mean Square Error (RMSE) to detect which of the methods adopted is better for population projection. RMSE of both geometric and exponential population projections are 1,832,610,950 and 1,930,404,821 respectively. The multiple bar chart was drawn which indicated higher increase in population projection for both geometric and exponential growth models.
VL  - 7
IS  - 3
ER  -

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Author Information

Oladimeji Olanrewaju Adedipupo

Department of Statistics, Federal Polytechnic, Ile-Oluji, Nigeria
Akomolafe Abayomi Ayodele

Department of Statistics, Federal University of Technology, Akure, Nigeria
Lasisi Taiwo Abideen

Department of Statistics, Ladoke Akintola University of Technology, Ogbomosho, Nigeria
Ojo Thompson Olabode

Department of Statistics, Federal Polytechnic, Ede, Nigeria
Adesina Oluwaseun Ayobami

Department of Statistics, Ladoke Akintola University of Technology, Ogbomosho, Nigeria
Egbedokun Gabriel Olumide

Department of Computer Science, The Polytechnic, Ibadan, Nigeria

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APA Style

Oladimeji Olanrewaju Adedipupo, Akomolafe Abayomi Ayodele, Lasisi Taiwo Abideen, Ojo Thompson Olabode, Adesina Oluwaseun Ayobami, et al. (2022). Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). International Journal of Systems Science and Applied Mathematics, 7(3), 46-51. https://doi.org/10.11648/j.ijssam.20220703.11

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ACS Style

Oladimeji Olanrewaju Adedipupo; Akomolafe Abayomi Ayodele; Lasisi Taiwo Abideen; Ojo Thompson Olabode; Adesina Oluwaseun Ayobami, et al. Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). Int. J. Syst. Sci. Appl. Math. 2022, 7(3), 46-51. doi: 10.11648/j.ijssam.20220703.11

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AMA Style

Oladimeji Olanrewaju Adedipupo, Akomolafe Abayomi Ayodele, Lasisi Taiwo Abideen, Ojo Thompson Olabode, Adesina Oluwaseun Ayobami, et al. Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE). Int J Syst Sci Appl Math. 2022;7(3):46-51. doi: 10.11648/j.ijssam.20220703.11

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@article{10.11648/j.ijssam.20220703.11,
  author = {Oladimeji Olanrewaju Adedipupo and Akomolafe Abayomi Ayodele and Lasisi Taiwo Abideen and Ojo Thompson Olabode and Adesina Oluwaseun Ayobami and Egbedokun Gabriel Olumide},
  title = {Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {7},
  number = {3},
  pages = {46-51},
  doi = {10.11648/j.ijssam.20220703.11},
  url = {https://doi.org/10.11648/j.ijssam.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20220703.11},
  abstract = {Nigeria, a developing nation is experiencing the overwhelming effects of her exponentially ever-increasing population. This paper is aimed at projecting the future population of Nigeria using the exponential and geometric growth models from 1991 and 2006 population censuses of Nigeria. The resultant effects are clearly evident for all stakeholders to see and feel. Researches have been carried out to study, explain and recommend likely solutions to the population growth of Nigeria. The data used in this research paper were extracted from the National Population Commission of Nigeria bulletin which was secondary data. The forecast for Geometric and Exponential models were made using last Nigeria population census 2006 as base population and projection were made from 2012 to 2022 and adopt the Root Mean Square Error (RMSE) to detect which of the methods adopted is better for population projection. RMSE of both geometric and exponential population projections are 1,832,610,950 and 1,930,404,821 respectively. The multiple bar chart was drawn which indicated higher increase in population projection for both geometric and exponential growth models.},
 year = {2022}
}

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TY  - JOUR
T1  - Detection of Appropriate Model for Nigeria Population Growth Using Root Mean Square Error (RMSE)
AU  - Oladimeji Olanrewaju Adedipupo
AU  - Akomolafe Abayomi Ayodele
AU  - Lasisi Taiwo Abideen
AU  - Ojo Thompson Olabode
AU  - Adesina Oluwaseun Ayobami
AU  - Egbedokun Gabriel Olumide
Y1  - 2022/08/17
PY  - 2022
N1  - https://doi.org/10.11648/j.ijssam.20220703.11
DO  - 10.11648/j.ijssam.20220703.11
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 46
EP  - 51
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20220703.11
AB  - Nigeria, a developing nation is experiencing the overwhelming effects of her exponentially ever-increasing population. This paper is aimed at projecting the future population of Nigeria using the exponential and geometric growth models from 1991 and 2006 population censuses of Nigeria. The resultant effects are clearly evident for all stakeholders to see and feel. Researches have been carried out to study, explain and recommend likely solutions to the population growth of Nigeria. The data used in this research paper were extracted from the National Population Commission of Nigeria bulletin which was secondary data. The forecast for Geometric and Exponential models were made using last Nigeria population census 2006 as base population and projection were made from 2012 to 2022 and adopt the Root Mean Square Error (RMSE) to detect which of the methods adopted is better for population projection. RMSE of both geometric and exponential population projections are 1,832,610,950 and 1,930,404,821 respectively. The multiple bar chart was drawn which indicated higher increase in population projection for both geometric and exponential growth models.
VL  - 7
IS  - 3
ER  -

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