Question: I need help with these questions using the data that I provided below. If you need more information lmk. Thanks This dataset is about medical

I need help with these questions using the data that I provided below. If you need more information lmk. Thanks

This dataset is about medical insurance costs: One dependent and two independent variables

age: age of primary beneficiary(X)
bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height, (X)
children: Number of children covered by health insurance / Number of dependents (X)
charges: Individual medical costs billed by health insurance (Y)

I need help with these questions using the data that I provided

below. If you need more information lmk. Thanks This dataset is about

A B C D E F G H SUMMARY OUTPUT N W Regression Statistics Multiple R 0.34655187 5 R Square 0.1200982 6 Adjusted R S 0.11811941 Standard Err 11372.3296 8 Observations 1338 10 ANOVA 11 df SS MS F Significance F 12 Regression 3 2.3548E+10 7849386749 60.6927547 8.80054E-37 13 Residual 1334 1.7253E+11 129329881 14 Total 1337 1.9607E+11 15 16 Coefficients itandard Errol t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 17 Intercept -6916.2433 1757.47967 -3.9353191 8.7368E-05 -10363.96835 -3468.5183 -10363.968 -3468.5183 18 age 239.994474 22.2888784 10.7674541 5.5339E-26 196.2694034 283.719545 196.269403 283.719545 19 bmi 332.083365 51.3104628 6.47203994 1.3549E-10 231.4253779 432.741351 231.425378 432.741351 20 children 542.864652 258.241271 2.1021607 0.03572625 36.26141725 1049.46789 36.2614173 1049.46789 21 22 23 24 25 263. Once you have the idea and the data, it is time to apply the LRM. Some issues you should inves- tigate and discuss are: o Are the variables that you thought could be important statistically signicant (at 5%)? o Are there variables that you would have liked to include in the regression but could not nd data for? Discuss Whether you expect these omitted variables to introduce bias in your OLS estimates. 0 Are the estimated effects (betas) of the expected sign? 0 Interpret the estimated effects 0 Are there one or more variables that you would like to exclude from the regression because they are irrelevant? Use the Ftest 0 Include at least one type of nonlinearity in the LRM and interpret its effect

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