This study was carried out with the purpose of proposing a construction of confidence intervals for the critical point of a second degree regression model using a parametric bootstrap methodology. To obtain the distribution of the critical point, height growth data of the plants were used. From the analysis, the theoretical variables for the error and the confidence intervals were constructed. In addition, we examined different variance expressions with the purpose of the bootstrap-t confidence interval. The point estimate of the critical point was 10.7423 g L-1 of fertilizer doses without growth of C. canjerana plants. It was verified that the confidence intervals that considered the expression of the variance with the covariance between the regression models, present more satisfactory results, that is, results with more precision.

The number of child deaths has been decreasing over the years, in the world, in Brazil and in Rio Grande do Sul. The intuition of this article is to identify the scenario of infant mortality in Rio Grande do Sul, verifying if it is reflected in its mesoregions. For this, descriptive statistics, correlation with Spearmam test and principal components techniques were performed. The results obtained in the descriptive analysis revealed that in general Rio Grande do Sul and its mesoregions behave the same way, the correlations were high among the variables, except with the variable, proportion of women who attended less than 7 prenatal consultations. Principal component analysis also showed that the mesoregion and state variables are explained by two components. Thus, it is concluded that in fact the scenario of infant mortality is reflected in its mesoregions.

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