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get_regression_summaries(peng3) r_squared= 0.769, adj_r_squared=0.767, mse= 0.8982379, rmse = 0.9477541, sigma= 0.953, statistic= 375.059, p_value= 0, df= 3. nobs= 342. Holding constant bill length, how much
get_regression_summaries(peng3) r_squared= 0.769, adj_r_squared=0.767, mse= 0.8982379, rmse = 0.9477541, sigma= 0.953, statistic= 375.059, p_value= 0, df= 3. nobs= 342. Holding constant bill length, how much difference in bill depth is there between Adelie penguins and Gentoo penguins? Using the penguins dataset, you regress bill_depth_mm (which is the depth of the penguin's bill in millimeters) on bill_length_mm (length of the penguin's bill in millimeters) and two dummy coded indicators to contrast the species (Gentoo penguins are the reference group). Use the output below to answer the following questions. ## Fit a multiple linear regression model. peng3 <- penguins %>% lm(bill_depth_mm ~ bill_length_mm + adelie_dm +chinstrap_dum, data = .) get_regression_table(peng3) term= intercept, estimate= 5.486, std_error, 0.835, statistic= 6.567, p_value= 0, lower_ci= 3.843, upper_ci= 7.130. term= bill_length_mm, estimate= 0.200, std_error, 0.017 statistic= 11.427, p_value= 0, lower_ci= 0.165, upper_ci= 0.234 term= adelie_dum, estimate= 5.106, std_error, 0.191, statistic= 26.674 p_value= 0, lower_ci= 2.886, upper_ci= 5.483 term= chinstrap_dum, estimate= 3.173, std_error, 0.146 statistic= 21.742, p_value= 0, lower_ci= 2.886, upper_ci= 3.460 get_regression_summaries(peng3) r_squared= 0.769, adj_r_squared=0.767, mse= 0.8982379, rmse = 0.9477541, sigma= 0.953, statistic= 375.059, p_value= 0, df= 3. nobs= 342. Holding constant bill length, how much difference in bill depth is there between Adelie penguins and Gentoo
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