Obtain the residual plots and cut and paste them into the report. Briefly comment on the appropriateness of your fitted model. (1) If the assumptions
Obtain the residual plots and cut and paste them into the report. Briefly comment on the appropriateness of your fitted model.
(1) If the assumptions are met and the fitted model is appropriate,continue to Step 2G.
(2) If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step 2G. Note -- you do not need to check the assumption of independence in your project. (That assumption is automatically met because your project is not time-dependent).
Simple Regression Modeling Steps 1. Open the Excel worksheet containing your Team Project Data. 2. As you learned in Module 2, run a simple linear regression model using the independent numerical variable whose Excel worksheet column is highlighted in DARK ORANGE as the predictor of Y the YELLOW Excel column. A. Cut and paste into your report the scatter plot and the Excel Regression Output for this simple linear regression model. B. Write the sample regression equation. C. Interpret the meaning of the Y-intercept and slope for your fitted model. D. Interpret the meaning of the coefficient of determination r 2. E. Interpret the meaning of the standard error of the estimate SYX. F. Obtain the residual plots and cut and paste them into the report. Briefly comment on the appropriateness of your fitted model. . (1) If the assumptions are met and the fitted model is appropriate, continue to Step 2G. . (2) If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step 2G. Note -- you do not need to check the assumption of independence in your project. (That assumption is automatically met because your project is not time-dependent). G. Comment on the statistical significance of your fitted model H. Comment on the 95% confidence interval estimate on the average impact on the response variable for each unit increase in the predictor variable. I. Select a value for your independent variable in its relevant range: 1. Predict y| A l. l) t l' H l J K L M N U I' 1 7 Price [in K) Age Features Corner7label 1 1 _ 310.0 13 7 N0 1 1 7 313.0 9 4 NO : 1 7 320.0 5 5 no 1 1 _ 320.0 3 5 no : 1 7 304.9 4 4 no 1 1 _ 295.0 4 4 N0 1 1 7 235.0 2 4 NO 1 1 _ 251.0 1 5 no 1 1 I_ 250.0 2 4 no 1 1 7 249.9 1 3 no : 1 ._ 242.5 4 5 N0 1 1 7 232.0 3 5 NO : 1 7 230.0 15 3 no 1 1 -_ 223.5 14 5 no 1 1 .7 222.0 13 3 no 1 1 _ 223.0 15 3 no 1 1 .7 220.5 15 4 NO 1 1 .7 215.0 15 3 YES 4001: v = 0111;571:1713933 1 17 213.9 17 4 YES 350.0 1 7 204.5 13 3 no 300.0 1 ._ 204.5 15 4 N0 1 7 202.5 10 3 ND 50.0 1 7 202.5 12 4 no E 200.0 1 -_ 195.0 15 2 was a 15011 ' Sqll 1 .7 201.0 17 5 no \"mm\A B C D m F G H 177.0 1050 48 NO 179.9 1733 43 NO 178.1 1299 40 NO 177.5 1140 36 YES 172.0 1181 37 4 OOOHO NO 320.0 2848 4 6 NO 264.9 2440 11 Ln NO 240.0 2253 23 4 NO 234.9 2743 25 5 YES 230.0 2180 17 YES 228.9 1706 14 4 OOOHH NO 225.0 1948 10 4 NO 217.5 1710 16 4 NO 215.0 1657 15 O NO 213.0 2200 26 4 NO 210.0 1680 13 4 NO 209.9 1900 34 NO 200.5 1565 19 NO 198.4 1543 20 NO 192.5 1173 6 4 NO 193.9 1549 5 4 NO 190.5 1900 3 NO 188.5 1560 CO YES 186.0 1365 10 NO 185.5 1258 YES 184.9 1314 NO 180.0 1338 YES 180.9 997 4 NO 180.5 1275 8 NO 180.0 1030 4 NO 178.0 1027 5 O W H NO 177.9 1007 19 NO 176.0 1083 22 NO 182.3 1320 18 NO NNUP 174.0 1348 15 NO 172.0 1350 12 NO 166.9 837 13 2 NO 234.5 3750 10 YES 202.5 1500 7 3 YES 198.9 1428 40 2 NO 187.0 1375 28 1 NO 183.0 1080 20 NO 182.0 900 23 NO RE DATA Variable INFO + adyF G B E I J C D H A 35 182.0 900 23 NO 175.0 1505 16 OHO 167.0 1480 19 NO 159.0 1142 10 NO 212.0 1464 7 NO 315.0 2116 25 NO 177.5 1280 14 NO 171.0 1159 23 NO 165.0 1198 10 NO 163.0 1051 15 NO 289.4 2250 40 NO 263.0 2563 17 NO 174.9 1400 45 YES 238.0 1850 YES 221.0 1720 OOOH HOO O O O O O H H O O O O O O O O O NO 932.6 215.9 1740 NO 217.9 1700 NO 02 210.0 1620 NO 209.5 1630 NO 210.0 1920 NO 05 207.0 1606 NO 205.0 1535 YES 208.0 1540 YES 08 202.5 1739 13 NO 1715 NO 09 200.0 199.0 1305 NO 197.0 1415 NO W / 199.5 1580 NO 192.4 1236 NO oooooo 192.2 1229 NO 15 192.0 1273 NO 191.9 1165 4 NO 181.6 1200 4 YES 18 178.9 970 A YES 19 22 23
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