A B C D E F G H I J K L M N O P 1 SUMMARY OUTPUT Regression Statistics Multiple R 0.895186 117.085+4.334*triceps-2.857 R Square 0.801359 6 Adjusted R Square 0.764113 7 Standard Error 2.479981 8 Observations 20 9 10 ANOVA L1 df SS MS F Significance F 12 Regression 3 396.9846 132.3282 21.51571 7.34326E-06 13 Residual 16 98.40489 6.150306 14 Total 19 495.3895 15 16 Coefficientsandard Err t Stat P-value Lower 95% Upper 95%ower 95.09 pper 95.0% 17 Intercept 117.0847 99.7824 1.1734 0.257808 94.44455 328.6139 -94.4146 328.6139 Triceps 4.334092 3.015511 1.437266 0.169911 -2.058506509 10.72669 -2.05851 10.72669 Thigh -2.85685 2.582015 -1.10644 0.284894 -8.330475789 2.61678 -8.33048 2.61678 20 Midarm -2.18606 1.595499 -1.37014 0.189563 -5.568367033 1.196247 -5.56837 1.196247 21 22A B C D E F G 1 Triceps H Thigh Midarm I J Bodyfat z-score K. outlier?' M N 0 P 19.5 43.1 29.1 11.9 Attribution: Data source: Applied Regression Models, (4th edition), Kutner, Neter, and Nachtsheim 24.7 49.8 28.2 22.8 30.7 51.9 37 18.7 in 29.8 54.3 31.1 20.1 19.1 Outlier Parameters 42.2 30.9 12.9 Calculate for Bodyfat Column QR -- 25.6 53.9 23.7 mean: 21.7 31.4 Lower Limit 58.5 27.6 27.1 median: 27.9 Upper Limit 52.1 30.6 mode: 25.4 10 22.1 # of outliers 49.9 23.2 21.3 standard deviation: 1 1 25.5 53.5 24.8 # of outliers 19.3 12 31.1 56.6 30 25.4 13 30.4 56.7 28.3 27.2 Run a multiple regression that predicts bodyfat based on midarm, thigh, and triceps measurements. 14 18.7 46.5 23 11.7 15 19.7 44.2 28.6 17.8 Write your equation here: 16 14.6 42.7 21.3 12.8 17 29.5 54.4 30.1 Using the model, provided, find the predicted body fat of someone who 23.9 has a triceps measurement of 21.4, thigh of 45.6, and midarm 18 27.7 55.3 25.7 22.6 measurement of 27.6. Show your work below: 19 30.2 58.6 24.6 25.4 20 22.7 48.2 27.1 14.8 21 25.2 51 27.5 21.1 22 23 74