please help me.

In this problem, we consider the UN1 1 a dataset, which is a subset of the UN1 1 dataset from the alr4 package. The UN1 1 a dataset contains the following measurements for n = 150 randomly selected countries and territories, mostly taken between 2009 and 2011. The variables are: region region of the world group a categorical variables with 3 levels: oecd for countries that are members of the Organization for Economic Co-operation and Development (OECD). africa for countries on the African continent, other for all other countries. (Note: No OECD countries are located in Africa) fertility number of children per woman ppgap Per capita gross domestic product (in US dollars) lifeExpF Female life expectancy (years) pctUrban Urban population percentage (e.g. 60 represents 60%) Consider the linear regression model ml for the female life expectancy lifeExpF on pctUrban and the linear and quadratic effects of log (ppgap) . Part of the model summary output from R is given below: > ml summary (ml) Call : Im (formula = lifeExpF ~ pctUrban + log (ppgap) + I(log (ppgap) ^2) , data = UNlla) Residuals: Min 10 Median 30 Max -25. 571 -1. 774 1. 385 3. 128 12.069Coefficients: Estimate Std. Error t value Pr (>It!) (Intercept) -12. 32887 13. 99467 -0. 881 0. 37978 pctUrban 0. 02092 0. 03592 XXXXX XXXXxxx log (ppgap) 15.27064 3. 42321 4. 461 1. 62e-05 * * * I (log (ppgdp ^2) -0. 61916 0. 20222 -3. 062 0. 00262 * * Signif. codes: 0 ' * * *' 0.001 ' * *' 0.01 .*' 0.05 . . ' 0.1 . ' Residual standard error: 6.207 on 146 degrees of freedom Multiple R-squared: 0. 6463, Adjusted R-squared: 0. 6391 F-statistic: 88.94 on 3 and 146 DF, p-value: F) lifeExpF ~ i) 9.213.4 N/A N/A N/A N/A pctUrban lifeExpF ~ 146 5,624.8 ii) iii) iv) 2. 27 x 10 pctUrban + log (ppgap) + I (log (ppgap) ^2)