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Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020
N.F. Adeleye1 , H.O. Ilo2 , T.O. Gbadamosi3
Section:Research Paper, Product Type: Journal-Paper
Vol.10 ,
Issue.2 , pp.38-45, Apr-2023
Online published on Apr 30, 2023
Copyright © N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi, “Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020,” International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.2, pp.38-45, 2023.
MLA Style Citation: N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi "Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020." International Journal of Scientific Research in Mathematical and Statistical Sciences 10.2 (2023): 38-45.
APA Style Citation: N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi, (2023). Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020. International Journal of Scientific Research in Mathematical and Statistical Sciences, 10(2), 38-45.
BibTex Style Citation:
@article{Adeleye_2023,
author = {N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi},
title = {Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020},
journal = {International Journal of Scientific Research in Mathematical and Statistical Sciences},
issue_date = {4 2023},
volume = {10},
Issue = {2},
month = {4},
year = {2023},
issn = {2347-2693},
pages = {38-45},
url = {https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=3121},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=3121
TI - Time Series Analysis of Crude Oil Production in Nigeria between the Years 2010 to 2020
T2 - International Journal of Scientific Research in Mathematical and Statistical Sciences
AU - N.F. Adeleye, H.O. Ilo, T.O. Gbadamosi
PY - 2023
DA - 2023/04/30
PB - IJCSE, Indore, INDIA
SP - 38-45
IS - 2
VL - 10
SN - 2347-2693
ER -
Abstract :
In Nigeria and other regions worldwide, crude oil is a crucial source of income and energy that necessitates careful attention and technical expertise in its production, refining, and global distribution. Throughout history, crude oil has been the cornerstone of Nigeria`s economy, playing a significant role in shaping its political, industrial, and economic future. According to reports, Nigeria`s petroleum sector is the nation`s biggest industry. This is likely a result of the widespread perception that petroleum is one of the main sources of energy all over the world. In addition to this, petroleum products make a wide range of additional contributions to national development, including the creation of jobs, revenue generation, earnings in foreign currencies, industrialization, and advancements in other economic indicators. The Nigerian National Petroleum Company Limited (NNPC Limited), formerly known as the Nigerian National Petroleum Corporation (NNPC), emerged in April 1977 out of merging the commercial and regulatory responsibilities of the Ministry of Petroleum Resources and the Nigerian National Oil Corporation (NNOC). Nigeria is Africa`s top producer of oil and gas. Using the Mann-Whitney test in our analysis section, it was discovered that there is a significant difference in crude oil production between the years 2010 and 2020. After the discovery that the time series data set was non-stationary using the Augmented Dickey-Fuller test, the Detrending method was applied to remove the trend in the dataset and transform it into a stationary dataset that would be suitable for prediction and forecasting. The Augmented Dickey-Fuller test was later used to test if the dataset is truly stationary. The Seasonal Autoregressive Integrated Moving Average (SARIMA) was used to test the model and was also used for the prediction and forecasting of the Crude Oil dataset. The result of the analysis indicates that SARIMA is a good statistical tool that can be used in the prediction of this kind of data (Crude Oil Data).
Key-Words / Index Term :
Augmented Dickey-Fuller Test, Mann Whitney Test, Detrending, Nigerian National Petroleum Company Limited (NNPCL), Seasonal Autoregressive Integrated Moving Average (SARIMA), Crude Oil.
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