Mathematical modeling of Taraba State population growth using exponential and logistic models

Abstract

The study models and simulates the future population growth of Taraba State using two models: exponential and logistic. Population data from 1991 to 2019 was obtained from the National Population Commission, and the models’ parameters were estimated and implemented using Python. The results showed that the exponential model performed better than the logistic model, with a higher R-squared value. Both models predict a growing population for Taraba State, reaching 9.8 million people by 2055, emphasizing the need for proper planning and policies to accommodate this growth. The study recommends that the state and federal governments use these findings to develop comprehensive plans for managing the increasing population.