ABSTRACT
This dissertation looked at the fertility rate, fertility pattern and some of the diseases that cause fertility problems which leads to pregnancy wastage and fertility differentials in women within the reproductive age using binary Logistic and Multiple regression. The result shows that the average Total Fertility Rate (TFR) of sample I, sample II and sample III are approximately five (5) children per woman, seven(7) children and six (6) children respectively. The histogram and the line graph of the three samplesindicate a gradual decline in TFR as the years increases. Result of logistic regression shows that Sexually Transmitted Disease (STD), Ectopic Pregnancy (ECT) and Ovarian Cyst (OVC) have a negative value which indicates decrease in Total Life Birth. Multiple regression result indicates a positive value in STD, FB and ECT while OVC is negative in sample I. In sample II, only STD is negative while FB, OVC and ECT are positive. Result of Sample III shows a positive value in STD, FB, OVC and ECT which indicate increase in Total Life Birth (TLB). Based on the result of the two methods used, binary logistic regression proved to be the best model for analyzing the data since the result is showing negative values in the variables STD, OVC and ECT which indicates decrease in fertility. While positive values in most of the variables in Multiple Regression result indicates increase in TLB.
TABLE OF CONTENTS
TITLE PAGE
TABLE OF CONTENTS
LIST OF FIGURES
LIST OF TABLES
ABSTRACT
CHAPTER ONE: INTRODUCTION
1.0 Introduction
1.1 Background of the study
1.2 Statement of Research Problems
1.3 Aim and Objectives of the Study
1.4 Significance of the Study
1.5 Scope of the Study
1.6 Definition of Terms
CHAPTER TWO: LITERATURE REVIEW
2.0 Introduction
2.1 Fertility in Nigeria
2.2 Report on Global Fertility Rate
CHAPTER THREE: MATERIALS AND METHODOLOGY
3.0 Introduction
3.1 Materials
3.2 Statistical Techniques and Modeling
3.2.1 Multivariate Analysis Techniques
3.2.2 Logistic Regression
3.2.3 Multiple Regression
3.3 Tests of Statistics
3.3.1 Normality Test
3.3.2 Test of Independence: Chi-square test
CHAPTER FOUR: RESULTS AND DISCUSSION
4.1 Introduction
4.2 Normality Test
4.3 Binary Logistic Regression
4.3.1 Binary logistic regression result of sample I
4.3.2 Binary logistic regression result of sample II
4.3.3 Binary logistic regression result of sample III
4.4 Multiple Regression
4.4.1 Multiple Regression results of sample I
4.4.2 Multiple Regression results of sample II
4.4.3 Multiple Regression results of sample III
4.5 Results and Discussion
CHAPTER FIVE: SUMMARY AND CONCLUSION
5.1 Summary
5.2 Conclusion
5.3 Suggestion for Further Research
REFERENCES
APPENDICES
CHAPTER ONE
1.0 Introduction
Fertility is one of the three principal components of population dynamics that determine the size and structure of the population of a country (Ramesh, 2010). Differentials in fertility behavior and fertility levels in different areas and among population strata or characteristics have been among the most pervasive findings in demography (Ramesh, 2010).
Fertility refers to the actual production of offspring, rather than the physical capability to produce which is termed fecundity. While fertility can be measured, fecundity cannot be. Demographers measure the fertility rate in a variety of ways, which can be broadly broken into "period" measures and "cohort" measures. "Period" measures refer to a cross-section of the population in one year. "Cohort" data on the other hand, follows the same people over a period of decades. Both period and cohort measures are widely used (Wikipedia, 2013).
Infertility is defined by the American Society for Reproductive Medicine (ASRM) as a disease of the reproductive system that impairs the body's ability to perform the basic function of reproduction. Many different factors and problems can cause infertility, including problems in the female reproductive system, the male reproductive system, or a combination of the two (UNTH, 2010).....
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Item Type: Postgraduate Material | Attribute: 86 pages | Chapters: 1-5
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