A Time Series Analysis Of Mean Temperature Of Umuahia South Local Government Area, Abia State

ABSTRACT

In this project work the temperature data for Umuahia South LGA inAbia State was analysed by the method of time series. Specifically, the method of simple descriptive time series analysis was employed while the multiplicative approach of separating the components was adopted. The method and approach helped us to construct a mathematical model that could be used in predicting future temperature values. The results of the test carried out in this work showed that all the four components of a time series were all present. The data maintained a constant trend for four years and thereafter slightly increased linearly for the remaining three years. It was also estimated that the product of cyclical and irregular components differs from one by less than 9%. Consequently CI was assumed to be unity. Finally, the trend and seasonal component were used in predicting the 1 999 temperature values. Conclusions were drawn based on the results of the study and recommendations were offered.

TABLE OF CONTENTS

Title

Dedication

Abstract

Cer rtification

Acknowledgement

Table of Contents

List of tables and figures

Chapter One

1.0 Introduction

1.1 Background of Study

1.2 Statement of problem

1 .3 Rationale of Study

1 .4 Objectives

1 .5 Scope of Study 4

1 .6 Literature Review 5

1 .7 Methodology 9

1 .8 Chapter Outline 13

1 .9 Definition of Concepts 14

Chapter Two

2.0 Justification of some Assumptions 16

2.1 Test for normality of the original data 16

2.2 Test for Homogeneity of Variance 18

2.3 Test for Randomness 20

Chapter Three

3.0 Estimation and Isolation of the Component of a time series. 22

3.1 Trend 22

3.2 Seasonal Variations 2,5

3.3 Cyclical Variation 28

3.3.1 Test for Serial Correlation in the residue 28

3.4 Irregular Component. 31

3.4.1 Justification of the Assumption of randomness in the irregular

component. 31

3.4.2 Justification of assumption of Zero mean. 32

Chapter Four

4.0 Forecasting, Summary Recommendations And Conclusion. 34

4.1 Forecasting 34

4.2 Summary 35

4.3 Recommendations 37

4.4 Conclusion 38

Bibliography 39

Appendices 41-50