Chapter One — 1.1 Background to the Study

Numerical Methods has become an increasingly important area of inquiry in the study of population growth models, as researchers seek a more precise, evidence-based understanding of how it shapes measurable outcomes.

Much of the existing literature on numerical methods draws on data and conditions that differ from the local context in which population growth models is typically studied or produced, limiting the direct applicability of prior findings to solution accuracy.

1.2 Statement of the Problem

There is currently limited empirical evidence on how numerical methods affects solution accuracy in population growth models, making it difficult for researchers and practitioners to draw reliable, context-appropriate conclusions. This study addresses that gap through a structured investigation.

1.3 Objectives of the Study

1. To determine the effect of numerical methods on solution accuracy of population growth models.
2. To evaluate the extent to which numerical methods influences solution accuracy.
3. To identify the conditions under which numerical methods has the greatest effect on solution accuracy.
4. To recommend practices based on the observed relationship between numerical methods and solution accuracy.

1.4 Research Questions

1. What is the effect of numerical methods on solution accuracy of population growth models?
2. To what extent does numerical methods influence solution accuracy?
3. Under what conditions does numerical methods have the greatest effect on solution accuracy?
4. What practices can be recommended based on this relationship?

1.5 Significance of the Study

This study is significant to researchers and practitioners working with population growth models, offering evidence on how numerical methods relates to solution accuracy. It also contributes to the broader literature in mathematics by documenting findings specific to the conditions under which the study was conducted.

1.6 Scope of the Study

The study is limited to examining Numerical Methods and its relationship with solution accuracy in population growth models, reflecting a BSc-level scope of analysis; conclusions are drawn strictly from the conditions and samples used in the study.