Health Sweets 92 76 84 56 73 48 98 96 70 27 63 49 72 57 66 98 69 84 78 55 Gender 1 4 4 6 6 8 2 4 6 8 7 5 5 8 7 2 7 3 8 6 1 2 2 1 2 2 1 1 1 2 1 2 2 2 1 2 1 1 1 1 BMI 21 23 25 31 22 28 22 23 26 35 27 29 26 27 25 19 32 27 28 26 SUMMARY OUTPUT Regression Statistics Multiple R 0.8853461706 R Square 0.7838378417 Adjusted R Square 0.7433074371 Standard Error 9.483474704 Observations 20 ANOVA df Regression Residual Total Intercept Sweets Gender BMI 3 16 19 SS 5217.9693206197 1438.9806793803 6656.95 Coefficients 169.8128315442 -3.0942266878 -9.6155410825 -2.634719701 Standard Error 17.8836115977 1.4020621779 4.3091119428 0.7836554692 In Chapter 16 Data Set 2, you will find scores on three variables. The outcome variable is overall health (Health) MS 1739.3231068733 89.9362924613 F Significance F 19.3395019883 1.430257109E-005 t Stat P-value 9.4954439497 5.61743719E-008 -2.2069111746 0.0422757005 -2.2314437894 0.040306269 -3.3620893424 0.0039649103 Lower 95% Upper 95% Lower 95.0% Upper 95.0% 131.9012685491 207.7243945394 131.9012685491 207.7243945394 -6.0664657285 -0.1219876471 -6.0664657285 -0.1219876471 -18.7504503249 -0.4806318401 -18.7504503249 -0.4806318401 -4.2959950828 -0.9734443191 -4.2959950828 -0.9734443191 variable is overall health (Health)- the higher, the more healthy. The predictor variables are preference for sweets (Sweets SUMMARY OUTPUT Regression Statistics Multiple R 0.8853461706 R Square 0.7838378417 Adjusted R Square 0.7433074371 Standard Error 9.483474704 Observations 20 ANOVA Regression Residual Total Intercept Sweets Gender BMI df -165.4625482511 588.9086164084 13294.9 Coefficients 193.2370452005 -2.9072992576 -9.2213110552 -2.5526164697 bles are preference for sweets (Sweets), with a higher number indicating \"I love'em\"; Gender, with 1 indicating male and 2 r, with 1 indicating male and 2 indicating female, and body mass index (BMI), a measure of obesity with higher numbers i ty with higher numbers indicating greater obesity. Use the analysis ToolPAK Regression tool to find out how well these pre d out how well these predictor overall health