(untitled) (FUDMA JOURNAL OF SCIENCES, 2024)
Growth models have been applied over time to track and forecast changes in variables such as population, body height, biomass, fungal growth, and other aspects of numerous fields of study. This research focuses on modelling the growth of Nigeria’s population from the year 1981 to 2021 and determining the best fit model to represent Nigeria’s population growth (male, female and total). Seven growth models were considered in this research which includes: the linear, the exponential (Malthusian), Logistic (Verhulst), Gompertz, Hyperbolic, Brody and the Von Bertalanffy growth models. The criteria used for comparison of best fitted model were the coefficient of determination (R2), Akaike Information Criterion (AIC), Mean Square Error (MSE), and Bayesian Information Criterion (BIC). The R2 showed that the exponential, the logistic and the Gompertz growth models were all better fits for Nigeria’s population (male, female and total) having the highest R2 (0.999). Further comparison with the MSE, AIC and BIC revealed that the exponential growth model best represented Nigeria’s population growth (male, female and total) having the least MSE, AIC and BIC. Hence the exponential growth model should be considered by researchers in Nigeria population projection.