Th e World Bank Indicators dataset includes data on 198 indicators from 209 countries from 1960 to the present. Among the variables reported by this dataset are the per capita GDP, the population growth rate, the percentage of rural population and the total tax rate (as a percentage of profi t). Shown here are the data for these fi ve variables for the most recent year available for the European Union countries for which data was available. Use the data to develop a regression model to predict per capita GDP from the population growth rate, the percentage of rural population and the total tax rate. Graph each of these predictors separately with the response variable and use Tukey’s four-quadrant approach to explore possible recoding schemes for non-linear relationships. Include any of these in the regression model. Comment on the regression model and its strengths and its weaknesses.

GDP per capita Population growth (constant 2000 USS) (% annual) (% of total) (% of profit) Rural population Total Tax Rate Country Austria 26,106.2 0.33 32.6 55.5 Belgium 24,176.4 0.75 2.6 57.3 Bulgaria 2,542.5 -0.50 28.6 31.4 Czech Republic 7,225.4 0.63 26.5 47.2 Denmark 30,547.9 0.65 13.1 29.2 Estonia 6,113.3 -0.02 30.5 49.1 Finland 26,495.9 0.47 36.4 47.7 France 22,820.1 0.54 22.4 65.8 Germany 24,409.5 -0.28 26.3 44.9 Greece 14,843,7 0.41 38.8 47.A Hungary 5,833.5 -0.16 32.1 57.5 Ireland 28,502.5 0.56 38.4 26.5 Italy 18,479.2 0.65 31.8 68.4 Lithuania 5,153.8 -0.55 32.9 42.7 Luxembourg 52,388.1 1.87 17.7 20.9 Netherlands 26,094.0 0.52 17.6 39.3 Poland 6,330.6 0.06 38.7 42.5 Portugal 11,588.1 0.09 39.9 42.9 Romania 2,606.6 -0.15 45.6 46.4 Slovak Republic 8,041.6 0.21 43.3 48.6 Slovenia 12,576.9 1.08 51.7 37.5 Spain 15,533.8 0.88 22.7 56.9 Sweden 30,899.3 0.89 15.4 54.6 United Kingdom 27,259.2 0.70 10.0 35.9