3. A study was conducted between 1958 and 1970 at the University of Chicago's Billings Hospital on the survival of patients who had undergone surgery for breast cancer. To estimate the axillary lymph nodes (axil nodes) of patients with a predictor variable 'age' using smf.ols function from the Python library statsmodels.formula.api we get the following results: OLS Regression Results Dep. Variable: axil nodes R-squared: 0. 004 Model: OLS Adj. R-squared: 0. 001 Method : Least Squares e-statistic: 1 . 210 Date : Sat., 02 Oct. 2021 Prob (F-statistic] : 0. 271 Time: 12:19:45 Log-Likelihood: -1036.7 No. Observations: 306 AIC: 2077. Df Residuals: 304 DIC: 2085. Df Model: Covariance Type: nonrobust == atd err PELLI [0 . 025 0.975] Intercept 6. 2316 2. 040 3. 055 0. DO2 2. 217 10.246 -0 . D420 D. 038 -1. 104 0 . 271 -0. 117 0. 033 Omnibus : 218 . 862 Durbin-Watson: 2. 065 Prob (Canibus) : 0. 000 Jarque-Bera (JB) : 2122 . 728 Skaw : 2.964 Prob ( JB) ; 0.00 Kurtosis: 14 - 461 cond. No . 266. (1). Is the model adequate for predicting the axillary lymph nodes (axil nodes) of patients? Comment. (ii) Express the fitted regression equation. Hence, interpret the estimated coefficients. (iii). Find out the significant variables (with justification) to estimate the axillary lymph nodes (axil nodes) of patients. (iv). Calculate the coefficient of determination. Hence, interpret the results. (v). Estimate the axillary lymph nodes (axil nodes) of patients when patient's age is 41 years