data test;
  length line $ 80;
  input line &; 
  firstchar = substr(line, 1, 1);
  rest_line = substr(line, 3, 77);
  if firstchar=">";
datalines;
> d <- read.csv( "data", header = TRUE, sep = "\t" )
> str(d)
'data.frame':   7 obs. of   4 variables:
 $ Name  : Factor w/ 7 levels "Bill","Jack",..: 5 3 6 4 1 7 2
 $ Height: num  6.2 5.5 5.7 5.6 5.8 6.1 6
 $ Weight: num  192 155 164 166 186 ...
 $ Gender: int  0 1 1 1 0 0 0
>
> mean( d$Weight )
[1] 180.1429
> mean( d[,3] )
[1] 180.1429
>
> mean( d$Weight[ d$Gender == 1 ] )
[1] 162.0333
> mean( d$Weight[ 2:4 ] )
[1] 162.0333
>
> d$Diff <- d$Height - mean( d$Height )
> print(d)
  Name Height Weight Gender        Diff
1  Joe    6.2  192.2      0  0.35714286
2 Jane    5.5  155.4      1 -0.34285714
3 Mary    5.7  164.3      1 -0.14285714
4 Jill    5.6  166.4      1 -0.24285714
5 Bill    5.8  185.8      0 -0.04285714
6 Pete    6.1  201.7      0  0.25714286
7 Jack    6.0  195.2      0  0.15714286
> summary(d)
   Name       Height          Weight          Gender            Diff
  Bill:1  Min.   :5.500   Min.   :155.4   Min.   :0.0000   Min.   :-3.429e-01
  Jack:1  1st Qu.:5.650   1st Qu.:165.3   1st Qu.:0.0000   1st Qu.:-1.929e-01
  Jane:1  Median :5.800   Median :185.8   Median :0.0000   Median :-4.286e-02
  Jill:1  Mean   :5.843   Mean   :180.1   Mean   :0.4286   Mean   : 2.538e-16
  Joe :1  3rd Qu.:6.050   3rd Qu.:193.7   3rd Qu.:1.0000   3rd Qu.: 2.071e-01
  Mary:1  Max.   :6.200   Max.   :201.7   Max.   :1.0000   Max.   : 3.571e-01
  Pete:1
>
> d$Gender <- factor( d$Gender, labels = c("M", "F") )
> summary(d)
    Name      Height          Weight      Gender      Diff
  Bill:1  Min.   :5.500   Min.   :155.4   M:4    Min.   :-3.429e-01
  Jack:1  1st Qu.:5.650   1st Qu.:165.3   F:3    1st Qu.:-1.929e-01
  Jane:1  Median :5.800   Median :185.8          Median :-4.286e-02
  Jill:1  Mean   :5.843   Mean   :180.1          Mean   : 2.538e-16
  Joe :1  3rd Qu.:6.050   3rd Qu.:193.7          3rd Qu.: 2.071e-01
  Mary:1  Max.   :6.200   Max.   :201.7          Max.   : 3.571e-01
  Pete:1
>
> plot( d$Height ~ d$Gender )
> plot( d$Height ~ d$Weight, xlab="Weight", ylab="Height" )

> m <- lm( d$Height ~ d$Weight )
> print(m)

Call:
lm(formula = d$Height ~ d$Weight)

Coefficients:
(Intercept)     d$Weight
    3.39918      0.01357

> abline(m)
> abline( mean(d$Height), 0, lty=2 )
;
proc print data=test;
run;