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For each question, as needed, submit the clean R code, the appropriate output, and interpret the results Do not submit R markdown files instead submit clean R codes Basic body measurements are taken 86 incoming female cadets one of the U.S. military academies. The variables measured are: ht height(cm) wt weight (kg) hip hip fore forearm circumfrence(cm) neck neck circumfrence (cm) wrist wrist circumfrence (cm) tri tricep skinfold (mm) scap scapular skinfold (mm) sup suprailiac skinfold (mm) fat body fat percent of body weight These data are available ir the file "bodyfat txt" We are interested in predicting (or estimating) the body fat, which the most difficult these variables measure. from the other nine variables. These data are from: Hocking R.R (1996), Methods and Applications of Linear Models}, New York: Wiley Table D12 pp. 708 710. Ohs ht wt wrist tri scap sup fat 1 173.4 57.8 91.8 21.1| 29.7 14.6112.2 12.1 22.9 26.9 2 173.6 70.5 99.3 27.5 31.5 152 165 164 264220.0 3 164.1 66.8 100.8 24.5 32.4 4 160.1 59.6 96.2 22.5 sul 14.9/28.2 91.4 24.6 31.5 15.2 18.1 13.8 17.9 21.7 7 165.1 643 98.3 23.7 32.1 14.8/24.0 8 167.3 89.3120.1 10 163.3 46.0 87.1 21.3 11 160.2 96.2 22.4 33.9| 83.9 21.6 29.9| 13 150.7 53.7 90.5 22.9 30.4 14 160.7 63.7| 97.8 24.8 32.4 25.8/17.7 16 158.7 61.4 96,8124,5 28.9 7 160.9 58.9 93.9 22.4 29.0| 14.0 20.3 95.3122.5 30.9| 85,6121.6 29.6 8.6] wrist 923122.5 29.2 99.51228 32.61 17.0 26 170.4 15. 30.4 15.0 92.1/24.1 30.6 24.2 23.3 88 26.8 94.5 23.6| s.o) 9.2 10.9 14.9 93.1 22.4 143/136 95679.9 32.6 78.0)114.424.332.3 14.6 34.1 15.0 14.8 13.0 822 23.5 12.9 18.0 8.8 9.7 26.4 87.7 20.9| 13.2)14.9) 15.5|16.432.0 9.8 10.0 29.3 43 166.1 31.8| 14.4 10.2 6.6 28.7 97.2.24.61318 15.0/18.2 15.5 15.2 14.7 10.0 134 24 15. 86,9121.4 97.51237 14.8139.7

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# rerad data from file
bodyfat = read.table("bodyfat.txt", header = T)

# create a linear models
bodyfat.lm = lm(fat~ ht + wt + hip +
                  fore + neck + wrist +
                  tri + scap + sup,
                data = bodyfat)...

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