One single excel file All the section should be addressed in the excel file Note this homework weight double The number of victories (W), earned run average (ERA), runs scored (R), batting average (AVG), and on base percentage (OBP) for each team in the American League in the 2012 season are provided in the following table The ERA is one measure of the effectiveness of the pitching staff, and a lower number is better The other statistics are measures of effectiveness of the hitters, and higher numbers are better for each of these W (Y) ERA (x1) R(x2) AVG OBP Team 1 93 3 9 712 0 247 0 311 Team 2 69 4 7 734 0 26 0 315 Team 3 85 4 02 748 0 255 0 318 Team 4 68 4 78 667 0 251 0 324 Team 5 88 3 75 726 0 268 0 335 Team 6 72 4 3 676 0 265 0 317 Team 7 89 4 02 767 0 274 0 332 Team 8 66 4 77 701 0 26 0 325 Team 9 95 3 85 804 0 265 0 337 Team 10 94 3 48 713 0 238 0 31 Team 11 75 3 76 619 0 234 0 296 Team 12 90 3 19 697 0 24 0 317 Team 13 93 3 99 808 0 273 0 334 Team 14 73 4 64 716 0 245 0 309 Develop a regression model that could be used to predict the number of victories based on the ERA Develop a regression model that could be used to predict the number of victories based on the runs scored Develop a regression model that could be used to predict the number of victories based on the batting average Develop a regression model that could be used to predict the number of victories based on the on base percentage Which of the four models is better for predicting the number of victories Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored, batting average, on base percentage Generate residual plots and Normal probability plot and discuss them Discuss the accuracy (r2) of the regression model you developed in section f, and the significance of independent variables (p value), interpret the sign of coefficients Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored, batting average, on base percentage with confidence level (CI) of 90 and discuss p values Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored with 95 CI and compare it with the developed model in section a, b and f (adjusted r2)

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One single excel file. All the section should be addressed in the excel file. Note: this homework weight double The number of victories (W), earned

One single excel file. All the section should be addressed in the excel file. Note: this homework weight double

The number of victories (W), earned run average (ERA), runs scored (R), batting average (AVG), and on-base percentage (OBP) for each team in the American League in the 2012 season are provided in the following table. The ERA is one measure of the effectiveness of the pitching staff, and a lower number is better. The other statistics are measures of effectiveness of the hitters, and higher numbers are better for each of these.

	W (Y)	ERA (x1)	R(x2)	AVG	OBP
Team 1	93	3.9	712	0.247	0.311
Team 2	69	4.7	734	0.26	0.315
Team 3	85	4.02	748	0.255	0.318
Team 4	68	4.78	667	0.251	0.324
Team 5	88	3.75	726	0.268	0.335
Team 6	72	4.3	676	0.265	0.317
Team 7	89	4.02	767	0.274	0.332
Team 8	66	4.77	701	0.26	0.325
Team 9	95	3.85	804	0.265	0.337
Team 10	94	3.48	713	0.238	0.31
Team 11	75	3.76	619	0.234	0.296
Team 12	90	3.19	697	0.24	0.317
Team 13	93	3.99	808	0.273	0.334
Team 14	73	4.64	716	0.245	0.309

Develop a regression model that could be used to predict the number of victories based on the ERA.
Develop a regression model that could be used to predict the number of victories based on the runs scored.
Develop a regression model that could be used to predict the number of victories based on the batting average.
Develop a regression model that could be used to predict the number of victories based on the on-base percentage.
Which of the four models is better for predicting the number of victories?
Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored, batting average, on-base percentage
Generate residual plots and Normal probability plot and discuss them
Discuss the accuracy (r2) of the regression model you developed in section f, and the significance of independent variables (p-value), interpret the sign of coefficients
Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored, batting average, on-base percentage with confidence level (CI) of 90% and discuss p-values
Develop a regression model that could be used to predict the number of victories based on the ERA, runs scored with 95% CI and compare it with the developed model in section a, b and f (adjusted r2)