Hi! I just need help with these questions! The background information is : below is computer output for three different regression models examining this relationship for countries in Central and South America. Child mortality is measured in deaths before age 5 per 1000 children born , and income is measured in US dollars per person. All algorithms are base ten

Q1-2.dock I. child mortality versus income Predictor Coet SE Coef Constant 34.149 9.297 10.05 0.000 Income per capita -0.0027295 0.0007530 -3.62 0.002 8 - 8. 35744 8-8q - 43.65 8-Bg(ed;) - 40.38 II. log(child mortality) versus income Predictor doef BE Coof Constant 1.53434 0.05580 27.50 0.DOD Income per capita -0.00005198 0.00001237 -4.20 0.001 8 - 0. 137280 8-89 - 51.08 -Bg(adj) - 60.18 III. log(child mortality) versus log(income) Predictor Coel SE Coel T P Constant 2. 9649 D. 3299 B. PP D. 000 Loy Income -0.46824 0.09476 -4.94 0.000 5 - 0.125578 R-Bg - 59.08 R-Bg (adj) - 56.58 a. Explain why the information provided suggests that a linear model may not be appropriate for describing the relationship between child mortality and income in these countries. b. Which model does the best job at summarizing the relationship between income and child mortality? Explain your reasoning c, Give the equation of the model you chose in part (b), using the transformed verabings) d. Use the model you chose in part (b) to predict the child mortality rate in a country with on inshome of $1300 per person