Regression Equation

body_mass_g	=	-459 +369.4bill_depth_mm

Coefficients

Term	Coef	SE Coef	T-Value	P-Value	VIF
Constant	-459	487	-0.94	0.348
bill_depth_mm	369.4	32.5	11.38	0.000	1.00

Model Summary

S	R-sq	R-sq(adj)	R-sq(pred)
351.766	51.71%	51.31%	50.06%

Analysis of Variance

Source	DF	Adj SS	Adj MS	F-Value	P-Value
Regression	1	16031778	16031778	129.56	0.000
bill_depth_mm	1	16031778	16031778	129.56	0.000
Error	121	14972470	123739
Lack-of-Fit	37	4360985	117864	0.93	0.583
Pure Error	84	10611484	126327
Total	122	31004248

Fits and Diagnostics for Unusual Observations

Obs	body_mass_g	Fit	Resid	Std Resid
14	5850.0	4934.8	915.2	2.61	R
15	4200.0	4934.8	-734.8	-2.10	R
18	6300.0	5156.5	1143.5	3.26	R
21	5700.0	4824.0	876.0	2.51	R
27	4100.0	4824.0	-724.0	-2.07	R
38	5250.0	5932.3	-682.3	-1.99		X
86	5600.0	5932.3	-332.3	-0.97		X

R Large residual X Unusual X

1. The first penguin in this sample had a bill depth of 13.2 mm. Using the regression equation you provided above, compute the predicted body mass for this penguin. Show your work.

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2. The first penguin in this sample had an actual body mass of 4500 grams. Using this value and the predicted value you computed in the previous question, compute the residual for the first penguin in this sample.

Hint: residual = actual body mass in the data set - predicted body mass