Regression Analysis of Factors Affecting Unemployment in Nigeria

Multiple regression study of factors driving unemployment in Nigeria using NBS data.

About this project

Uses NBS time-series data to estimate a multiple regression model of unemployment with GDP growth, inflation, government expenditure, and FDI as predictors.

Methodology

Regression (quantitative)

Chapters 1–5 outline

Chapter 1

Introduction: background to regression modelling of unemployment, statement of the problem (Nigeria's rising unemployment rate threatens economic stability), aim and objectives, research questions, scope, significance of the study, and definition of terms.

Chapter 2

Literature Review: theoretical framework, review of related works on regression modelling of unemployment, gaps in existing studies, and a summary positioning this project.

Chapter 3

Methodology / System Analysis and Design: OLS multiple regression in SPSS/EViews; diagnostic checks. Includes data collection method, system requirements, use-case and architecture diagrams (or population, sample size, and instrument).

Chapter 4

Implementation and Results: presentation of regression coefficients and interpretation. Presentation of findings, testing, evaluation, and discussion of results.

Chapter 5

Summary, Conclusion and Recommendations: key findings, contribution to knowledge, limitations, and recommendations for further research.

Get this project done — chapters, code, defence support

Final Year writes the full project for you. Original content, on time, with chat support up to defence day.

Start this project