A BSTRACT

In this work Time Series Analysis on the reported criminal cases in Ahia State (2000-2004) was carried out. The ultimate objective was to get a suitable inodle which would be used to forecast crime in Nigeria. Specific objectives arc to find trend and seasonality. In the result, we were able to find out that (1) Components on Time Series were present in the data (2) the rate of crime is on the increase (3) the season that had the lowest crime Rate is the 3 quarter (July, Aug. Sept) and the season that had the highest crime rate was the 4th quarter (Oct. Nov, Dcc). From the results, we suggest that problem of combat of crime should go down to families, small firms, parasatals and government; this combat should be to have sanity in every walks of life. Also, that the law enforcement agencies should not be left at the mercy of the criminal minded people arid the law enforcement agencies should be equipped with more sophisticated weapons which should be used to combat crime and not to be used for collecting bribe and stealing. With these and more recommendation made in this work, we hope that this mess which has eaten into the fabrics of our society will be eradicated.

TABLE OF CONTENTS

Title page

Dedication  ii

Acknowledgement

Abstract

Table of contents

List of figure

CHAPTER ONE

1.1 History 1

1.2Aim and Objectives 4

l.3Litcrature Review 5

CHAPTER TWO

2. 1 Data Collection 8

2.2 Method Of Analysis For This Study Is The Time Series Analysis. 8

2.2.1 Definition of Concepts 12

2.2.2 Problems Encountered 13

2.3 Justification of Some Assumptions 14

2.3.1 Test for Normal Tip of the Original Data 14

2.3.2 Test for Randomness of the Original Data 16

2.3.2 Examination of the Variance of the Original Data 17

CHAPTER THREE

3.0 Analysis 18

3.1 Measurement of the Trend 18

3.2 Dctrcndiiig 24

3.3 Measurement of Seasonal Variation 25

3.4 Deseasonalization 28

3.4. 1 cycheal- Irregular Components (Detrended-Deseasonalized Series) 30

3.4.2 Measurement of Cyclical Variation (Ct). 32

3.5 Measurement of Irregular Variation (It). 35

CHAPTER FOUR

Discussion

4.2 Observation and Interpretation of Result 36

4.1.ltrend 36

4.1.2scasonal index 37

4.l.3cyc1ie Irregular 37

4.2 Forecasting 3S

4.3 Summary 39

4.4.0 Conclusion and Recommendation 40

4.4.1 conclusion 40

4.4.2 Recommendation 42

Bibliography 60