st 1 Analysis with Minitab Regression Analysis Capacity

st 1 Analysis with Minitab Regression Analysis: Capacity versus Age, Height, . . . The regression equation is Capacity = - 6. 17 - 0. 0140 Age + 0. 149 Height + 0. 00636 Weight - 0. 0087 Chest - 0. 0220 Waist + 0. 343 Activity - 0. 109 Smoke - 0. 409 Gender 40 cases used 1 cases contain missing values Predictor Constant Age Height Weight Chest Waist Activity Smoke Gender S = 0. 4607 1 Coef -6. 172 -0. 014032 0. 14856 0. 006359 -0. 00867 -0. 02197 0. 3427 -0. 1092 -0. 4086 SE Coef 2. 653 0. 007000 0. 03503 0. 006094 0. 05791 0. 04557 0. 1282 0. 1491 0. 2757 R-Sq = 84. 3% T -2. 33 -2. 00 4. 24 1. 04 -0. 15 -0. 48 2. 67 -0. 73 -1. 48 P 0. 027 0. 054 0. 000 0. 305 0. 882 0. 633 0. 012 0. 469 0. 148 R-Sq(adj) = 80. 2%

Analysis - nd 2 with Minitab Notice that the P-values on the right suggest that only the predictors height (P-value = 0. 000) and activity level (P-value = 0. 012) are significant at the 0. 05 level of significance. The only other variable that seem possibly significant are age (Pvalue = 0. 054 and gender (P-value =0. 148). When stepwise regression techniques are applied using Minitab, the variables that remain significant are height, activity level, age and gender. The output is on the next two slides. 2

Analysis - nd 2 with Minitab Stepwise Regression: Capacity versus Age, Height, . . . Alpha-to-Enter: 0. 1 Alpha-to-Remove: 0. 1 Response is Capacity on 8 predictors, with N = 40 N(cases with missing observations) = 1 N(all cases) = 41 Step Constant Height T-Value P-Value Activity T-Value P-Value 3 1 -10. 251 2 -9. 759 3 -9. 787 4 -6. 929 0. 209 10. 42 0. 000 0. 191 9. 87 0. 000 0. 198 10. 43 0. 000 0. 161 6. 55 0. 000 0. 35 2. 87 0. 007 0. 31 2. 60 0. 013 0. 30 2. 67 0. 011

Analysis - nd 2 Activity T-Value P-Value with Minitab 0. 35 2. 87 0. 007 Age T-Value P-Value 0. 31 2. 60 0. 013 0. 30 2. 67 0. 011 -0. 0109 -1. 96 0. 057 -0. 0137 -2. 54 0. 016 Gender T-Value P-Value S R-Sq(adj) C-p 4 -0. 47 -2. 24 0. 032 0. 534 74. 06 73. 38 15. 1 0. 490 78. 78 77. 63 7. 8 0. 472 80. 84 79. 24 5. 8 0. 448 83. 23 81. 32 3. 0

Analysis - nd 2 with Minitab The resulting Minitab output from the regression analysis using those 4 predictors follows. Regression Analysis: Capacity versus Height, Activity, Gender, Age The regression equation is Capacity = - 6. 93 + 0. 161 Height + 0. 302 Activity 0. 466 Gender - 0. 0137 Age 40 cases used 1 cases contain missing values Predictor Constant Height Activity Gender Age 5 S = 0. 4477 Coef -6. 929 0. 16079 0. 3025 -0. 4658 -0. 013744 SE Coef 1. 708 0. 02454 0. 1133 0. 2082 0. 005404 R-Sq = 83. 2% T -4. 06 6. 55 2. 67 -2. 24 -2. 54 P 0. 000 0. 011 0. 032 0. 016 R-Sq(adj) = 81. 3%

Analysis - 2 nd with Minitab Consider the following graphs: residuals vs fits and the normal plot of the residual. 6