Question

I need the code in SAS and R and outputs please

2. The data below come from a study investigating a method of measuring body composition, and give the body fat percentage (% fat), age and sex for 18 adults aged between 23 and 61 years. Source: Mazess, R.B., Peppler, W.W., and Gibbons, M. (1984) Total body composition by dual-photon (153GD) absorptiometry. American Journal of Clinical Nutrition, 40, 834-839.

age	% fat	sex
23	9.5	male
23	27.9	female
27	7.8	male
27	17.8	male
39	31.4	female
41	25.9	female
45	27.4	male
49	25.2	female
50	31.1	female
53	34.7	female
53	42.0	female
54	29.1	female
56	32.5	female
57	30.3	female
58	33.0	female
58	33.8	female
60	41.1	female
61	34.5	female

a Enter the data into SAS using a DATALINES statement in the DATA step. Use PROC PRINT to print the resulting data set. Report your output.

b Create a data frame in R for the body composition data (from part a). Print the data frame and report the output.

Answer 1

(a) SAS code:

data mydata;
input age fat sex$;
datalines;
23 9.5 male
23 27.9 female
27 7.8 male
27 17.8 male
39 31.4 female
41 25.9 female
45 27.4 male
49 25.2 female
50 31.1 female
53 34.7 female
53 42.0 female
54 29.1 female
56 32.5 female
57 30.3 female
58 33.0 female
58 33.8 female
60 41.1 female
61 34.5 female
;
run;
proc print data=mydata;
run;

SAS-OUTPUT:

Obs	age	fat	sex
1	23	9.5	male
2	23	27.9	female
3	27	7.8	male
4	27	17.8	male
5	39	31.4	female
6	41	25.9	female
7	45	27.4	male
8	49	25.2	female
9	50	31.1	female
10	53	34.7	female
11	53	42.0	female
12	54	29.1	female
13	56	32.5	female
14	57	30.3	female
15	58	33.0	female
16	58	33.8	female
17	60	41.1	female
18	61	34.5	female

(b) R-code:

data.frame(age=c(23,23,27,27,39,41,45,49,50,53,53,54,56,57,58,58,60,61),fat=c(9.5,27.9,7.8,17.8,31.4,25.9,27.4,25.2,31.1,34.7,42.0,29.1,32.5,30.3,33.0,33.8,41.1,34.5),sex=c("male","female","male","male","female","female","male","female","female","female","female","female","female","female","female","female","female","female"))

R-OUTPUT:

1 23 9.5 male
2 23 27.9 female
3 27 7.8 male
4 27 17.8 male
5 39 31.4 female
6 41 25.9 female
7 45 27.4 male
8 49 25.2 female
9 50 31.1 female
10 53 34.7 female
11 53 42.0 female
12 54 29.1 female
13 56 32.5 female
14 57 30.3 female
15 58 33.0 female
16 58 33.8 female
17 60 41.1 female
18 61 34.5 female