CORRELATION AND REGRESSION ANALYSIS OF THE EXPENDITURE ON ADVERTISEMENT AND AMOUNT REALISED ON SALES

Description

ABSTRACT

correlation and regression analysis of the expenditure on advertisement and amount realised on sales. The objective of the study is to understand and critically examine whether there is a relationship between advertisement and sales of Osogbo Steel Rolling Company, Osogbo for the period of ten years 19912000, using the method of correlation and regression analysis. The method of analysis used in this project is the regression and correlation. Under this, we discussed the least square method of estimation which is considered to be the standard method of obtaining a regression line because it is mathematically based. The least square method is given as: Y a bxi ei a significance test of hypothesis, that is regression coefficient b which is being estimated by b was also carried out to test the relationship between the advertisement and sales. Interval estimation in simple linear regression and method of estimating correlation were also discussed. All the test carried out was at the 5 level of significance. Finally, analysis of variance was also used to test the relationship between advertisement and sales. The tests carried out are significant.

TABLE OF CONTENT

Title Page…………………………………………………………………………………………………. i

Certification.. iii

Dedication.. iv

Acknowledgement v

Table of Content vi

Abstract viii

Chapter One. 1

1.0 General Introduction.. 1

1.1 The Statement of the Problem.. 2

1.2 Hypothesis. 3

1.3 Significance of the Study. 4

1.4 Aims and Objectives. 5

1.5 Definition of Terms. 5

1.6 Abbreviation Used. 6

1.7 Limitation of the Study Scope and Coverage7

Chapter Two.. 8

2.0 Literature Review.. 8

Chapter Three. 15

3.0 Research Methodology. 15

3.1 Data Collection.. 15

3.1.1 Source of Data. 15

3.1.2 Problem Encountered. 16

3.1.3 Types of Data. 17

3.1.4 Method of Data Collection.. 19

3.2.0 Regression Analysis. 20

3.2.1 Method of Fitting Regression Line. 21

3.2.2 Interpretation of Regression Equation and Line. 27

3.2.3 Analysis of Variance ANOVA32

3.2.4 Confidence Interval for a and b. 34

3.3 Correlation.. 36

3.3.1 Correlation Coefficient37

3.3.2 Spearman Rank Correlation Coefficient39

3.3.3 Product Moment Correlation Coefficient40

3.3.4 Interpretation of Correlation Coefficient41

3.3.5 Test of Hypothesis. 42

Chapter Four. 43

4.0 Data Presentation and Analysis. 43

4.2 Confidence Interval for and b. 47

4.3 Test of Hypothesis for a and b. 51

4.4 Analysis of Variance Approach.. 53

4.5 Correlation Coefficient using Karl Pearsons Product Moment Correlation Coefficient.55

4.6 Computation of Rank Correlation using Spearmans Approach.. 57

Chapter Five. 64

5.0 Findings, Conclusion and Recommendation.. 64

5.1 Findings of Study. 64

5.1 Conclusion.. 65

5.2 Recommendation.. 67

References. 69