MULTIVARIATE TECHNIQUES IN CRIME DATA ANALYSIS: AN ASSESSMENT OF UTILIZED AND ALTERNATIVE STATISTICAL METHODS
MULTIVARIATE TECHNIQUES IN CRIME DATA ANALYSIS: AN ASSESSMENT OF UTILIZED AND ALTERNATIVE STATISTICAL METHODS
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Date
2015-05-20
Authors
Osi, Abdulhameed A.
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Abstract
The scope of crime and the concern for its prevention/control has grown
considerably in the last few years in Nigeria. Therefore, how to discover the variables
which have salience in affecting crime rate has become crucial. In this thesis, some of
Multivariate Statistical Techniques were utilized on the crime data of Nigeria.
Specifically, Principal Component Analysis (PCA) is used to discover the distinct
influential variables in the identification of State with high or low crime rate;
evaluates and compares the performances of five different Classification Techniques
(i.e., Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA),
K-Nearest Neighbour Analysis (KNN), Classification Trees (CT) and Logistic
Discriminant Analysis (LgDA)) in the classification of States of Nigeria as high and
low crime rate (unsafe and safe). Each method has unique assumptions about the data,
so each may be appropriate for different situations. The results show that four
Principal components have been retained using both scree plot and Kaiser’s criterion
which accounted for 75.024% of the total variation. QDA had the best overall
classification performance by classifying 100% of the States correctly, followed by
LDA which had only 13.9% apparent error rate. LgDA is recommended to be used
when QDA assumption failed while CT are the recommended alternative when
LDA’s assumptions are not met. Though CT’s performance is likely lower than that
of LDA, it offers many advantages that make it a useful method, such as its lack of
data assumptions.
Description
A THESIS SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES,
AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE AWARD OF MASTERS DEGREE IN STATISTICS
Keywords
MULTIVARIATE,, TECHNIQUES,, CRIME,, DATA ANALYSIS:,, ASSESSMENT,, UTILIZED,, ALTERNATIVE,, STATISTICAL,, METHODS.