Distribution functions, their properties and interrelationships play a significant role in modeling naturally occurring phenomena. Numerous standard distributions have been extensively used over the past decades for modeling data in several fields, however, generalizing these standard distributions has produced several compound distributions that are more flexible compared to the baseline distributions. Acquired immune deficiency syndrome is a disease caused by human immunodeficiency virus (HIV) that leads to a continuous decay of the human body immune system. Over the past few years, the rate of mother-to-child transmission of HIV has been on a non-decreasing trend in Nigeria and hence becoming a threat to the health of the nation. The Weibull generalized family of distributions has been efficient in developing new continuous probability distributions with additional two shape parameters. In this paper, a Weibull-based model has been proposed and it is called “a Weibull-Exponential Inverse Exponential distribution”. The properties, estimation of parameters and application of the new distribution are presented and discussed in this paper. Adequate application and investigation of the new model was done using a dataset on the rate of mother-to-child transmission of HIV and the result was compared with that of other competing models.

Fertility behavior is conditioned by both biological and social factors. Knowledge of fertility pattern gives insight into drivers of human fertility. The paper investigated the birth pattern of women in Kebbi State, North Western Nigeria. A total of 2,256 questionnaires were distributed to the women of child bearing age using simple random sampling across five local government areas. The aim of the study was to analyze the pattern of fertility among age group of women of childbearing age and the effects of some exogenous variables on the fertility of women in the state. Poisson regression was applied for the positive count value recorded. The results from the analysis revealed that experience of birth or history of birth, financial reliant, obesity, individual age are highly significant to the study and have direct impact on fertility. Despite our ability to breed continuously, all human populations exhibit variation in reproduction.

The study aimed at investigating the effects of demographic parameters on both economic and population growth in Nigeria. Three models were employed in the study and results from model 1 depicted that economic growth has a positive effects to BR and negatively affected by DR, these results had demonstrated that increase in population growth in Nigeria is favorable to economic growth of the nation while death was found unfavorable to the economic growth in Nigeria. This result is an indication of the fact that Nigeria is not facing the problem of overpopulation; rather the capacities of Nigerian Government and responsible organizations to create a favorable economic environment by channeling the right resources into the right place. In the second model we also discovered that labor force was statistically significant with a P-value of 0.00328. Thus, model 3 regressed GDP, labor force, health expenditure and corruption perception on population growth. The results depicted that all, except health expenditure with 0.82552 P-value, are statistically significant. The results have shown the influence of economic growth, labour force and corruption on the growth of population in Nigeria. The data in this work were of two types from three different sources; National Bureau of Statistics (NBS), African Development Bank (ADB) and World Bank (WB), first part ranges from 1995 to 2018 and second part ranges from 1985 to 2018.

This study deals with using calibration estimation approaches to modified the combined ratio estimator in stratified random sampling. Calibration distance measures with their associate constraints were used to modify combined ratio estimator. In stratified random sampling, new sets of optimum calibration weights are created and used to obtain new calibration estimators of population mean.  Empirical study through simulation was conducted to look into the efficiency of the suggested estimators obtained. The suggested calibration estimators are more efficient than other existing estimators investigated in the study, according to the findings.

This study considered modification of combined ratio type calibration estimators in stratified random sampling using calibration estimation approaches. The estimators of population mean in stratified random sampling depends on the strata estimated sample means. However, the means are sensitive to the extreme values or outliers in the sample observations of the study variables and strata sizes respectively. A new sets of calibration weights and property of the suggested combined calibration estimators of population mean in stratified sampling were derived. Empirical study through simulation was conducted to investigate the efficiency of the modified combined ratio-type calibration estimators of population mean obtained and the results revealed that the suggested estimators of population mean performed better than some existing estimators considered in the study.

This article presents a comprehensive study of an odd Lindley-Gompertz distribution which has already been proposed in the literature but without any properties. The present study unlike the previous one has considered the derivation of several properties of the odd Lindley-Gompertz distribution with their graphical representations and discussions which has not been done in the first proposition of the distribution.  The study looks at properties such as survival (or reliability) function, the hazard function, the cumulative hazard function, the reverse hazard function, the odds function, quantile function, moments, moment generating function, characteristic function, cumulant generating function, distribution of order statistics and maximum likelihood estimation of the distribution’s parameters none of which was treated by the previous author of the model. An illustration to evaluate the goodness-of-fit of the odd Lindley-Gompertz distribution has also been done using two real life datasets and the results show that the model fits the datasets better than the five other distributions considered in this present study.

Some existing estimators based on auxiliary attribute have been proposed by many authors. In this paper, we use the concept of power transformation to modify some existing estimators in order to obtain estimators that are applicable when there is positive or negative correlation between the study and auxiliary variable. The properties (Biases and MSEs) of the proposed estimators were derived up to the first order of approximation using Taylor series approach. The efficiency comparison of the proposed estimators over some existing estimators considered in the study were established. The empirical studies were conducted using existing population parameters to investigate the proficiency of the proposed estimators over some existing estimators. The results revealed that the proposed estimators have minimum Mean Square Errors and higher Percentage Relative Efficiencies than the conventional and other competing estimators in the study. These implies that the proposed estimators are more efficient and can produce better estimates of the population mean compared to the existing estimators considered in the study.

Nigeria’s effort to reduce under-five mortality has been biased in favour of childhood mortality to the neglect of neonates and as such the literature is short of adequate information on the determinants of neonatal mortality, whereas studies have shown that about half of infant deaths occur in the neonatal period. Knowledge of the determinants of neonatal mortality is essential for the design of intervention programmes that will enhance neonatal survival. Therefore, this study was conducted to investigate the trends in neonatal mortality in Nigeria. It also proposed a Poisson based continuous probability distribution called Poisson-Lindley distribution to neonatal mortality rate in Nigeria. Some properties of the new model and other relevant measures were obtained. The unknown parameters of the model were also estimated using the method of maximum likelihood. The fitness of the proposed model to the neonatal mortality rate was considered using a dataset on neonatal mortality rate from 1967 to 2019.