Application of Principal Component Analysis to Crime Data, Case Study: Mathare Slums, Nairobi County in Kenya
American Journal of Theoretical and Applied Statistics
Volume 8, Issue 1, January 2019, Pages: 7-17
Received: Jan. 8, 2019;
Accepted: Jan. 28, 2019;
Published: Feb. 21, 2019
Views 329 Downloads 125
Wafula Mike Erick, Department of Mathematics and Actuarial Science, Kenyatta University (KU), Nairobi, Kenya
Samson Wangila Wanyonyi, Department of Mathematics, University of Eldoret, Eldoret, Kenya
Chris Muchwanju, Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya
Follow on us
The study focuses on statistical analysis of causes of crimes in Mathare slums, Nairobi county using data collected via questionnaires in April 2018.The Correlation analysis was carried out to explain the association between the causes of crimes while the principal component analysis (PCA) was used to reduce the dimensionality of the data sets. The Correlation analysis indicates a fairly strong positive relationship between unemployment and drugs and substance abuse which means that their variables can be used to predict one another. PCA analysis reveals that three PCs (drugs and substance abuse, unemployment and neglect from parents) that explains about 52.6% of the total variability of the causes of crimes against person are suggested to be retained. Similarly, two PCs (drugs and substance abuse and unemployment) that explain about 42.2% of the total variability of the causes of crimes against property are suggested to be retained. Generally, the causes of crimes against person and property in Mathare slums are not unique.
Crime, Principal Component Analysis, Total Variation, Scree Plot
To cite this article
Wafula Mike Erick,
Samson Wangila Wanyonyi,
Application of Principal Component Analysis to Crime Data, Case Study: Mathare Slums, Nairobi County in Kenya, American Journal of Theoretical and Applied Statistics.
Vol. 8, No. 1,
2019, pp. 7-17.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fajemirokun F., Adewale O., Idowu T., Oyewusi A. and Maiyegun B. (2006). A GIS Approach to Crime Mapping and Management in Nigeria: A case study of Victoria Island Lagos, CBN. Journal of Applied Statistics, Vol.3 No.2 49, .www.oicf.org.
Aki Stravra, (September 2002). Crime on Nairobi: Results of a City wide victim survey. UN Habitat (safer cities: series 4), Nairobi.
Masese Grace (2007). Crime and Violence Trends in Nairobi, Kenya. Case study prepared for Enhancing Urban Safety and Security: Global Report on Human Settlements 2007. UN Habitat 2007.
GOK and UNDP (2010-2013). Report on overview of crime incidents in Nairobi Region Security Research Information Centre (SRIC).
Rev. Fr. Dr. Ndikaru Wa Teresia (2011). Crime causes and victimization in Nairobi city slums. International journal of current research, 3 (12) 275-285.
Darkey D. and Kariuki A. (2013). A study on Quality of Life in Mathare, Nairobi Kenya. Journal of Human Economic Development. 41 (3) 207-219.
Andvig J. C and Barasa T. (2014). A political Economy of slum spaces: Mathare valley. Norwegian Institute of International Affairs. Norway.
Chris Muchwanju, Joel C. Chelule and Joseph Mung’atu (2015). Modelling crime rate using a mixed effect regression model. American journal of Theoretical and Applied statistics. 4 (6), 496-503.
Wanjiru M. W and Matsubara K. (2017). Slum toponymy in Nairobi, Kenya. A case study analysis of Kibera, Mathare and Mukuru. Urban and Regional Planning review, 4.
Mburu L. W (2014). Modeling and mapping crime in Eastern Nairobi, Kenya. GIScience Research Group. University of Heidelberg.
Jolliffe, I. T (2002).Principal Component Analysis, 2nd Edition, Springer-Verlag, New York.
Rencher, AC. (2002). Methods of Multivariate Analysis, 2nd edition, John Wiley & Son, New York. Richard, A.J. and Dean, W. W. (2001). Applied Multivariate Statistical Analysis, 3rd edition, Prentice-hall, New Dehli.
Kendall Williams and Ralph Gedeon (2004), A Multivariate Statistical Analysis of Crime Rate in US Cities.
Yusuf Bello, Yusuf U. Batsari and Abdullahi S. Charanchi (2014). Principal Component Analysis of Crime Victimizations in Kastina Senatorial zone. International journal of science and Technology,3 (4).
Olufolabo O. O.,Akintande O. J., Ekum M. I. (2015). Analysing the Distribution of crimes in Oyo State using Principal Component Analysis. IOSR Journal of Mathematics (IOSR-JM) Vol.11 Issue 3.
Soren, H. (2006). Example of multivariate analysis in R-Principal Component Analysis (PCA).
Perry. R. H., Charlotte, B., Isabell M. and Bob, C. (2004).SPSS Explained, ISBN: 0-203-67627-0, Routledge, Taylor &Francis Group, London &New York.