options nodate nonumber pagesize=60;
data d1;
input gender well hassles anger;
* drop missing people*;
if _N_ = 23 then delete;
if _N_ = 30 then delete;
if _N_ = 73 then delete;
if _N_ = 91 then delete;
if _N_ = 96 then delete;
if _N_ = 142 then delete;
if _N_ = 182 then delete;
**************************************************
* Gender 1 = male 2 = female;
* Well = well being scale (high is good)
* Hassles = irritation scale (high is bad)
* Anger = trait anger (high is mad)
* Sample of working adults.
******************************************************;
*   Relate well being to hassles and anger
*    for the entire sample.  Find the correlation
*    matrix and regression of well being on hassles
*    and anger.  What is important?  Why?
******************************************************;
cards;
1 20 42 50
2 26 50 50
2 14 64 62
1 20 40 56
2 30 30 38
1 22 32 46
1 28 60 52
1 20 53  .
2 28 39 52
2 32 20 34
1 32 44 54
2 22 44 48
2 16 65 60
1 22 44 52
2 28 30 36
. 24 34 42
1 26 62 58
2 24 44 56
1 24 42 49
1 24 40 52
1 24 44 56
2 22 48 54
2 36 30 28
2 32  . 54
2 22 50 50
1 30 54 64
1 20 40 52
1 34 32 32
1 30 32 44
1 18 63 52
2 19 44 50
2 19 44 48
2 32 28 34
1 24 42 52
2 28 50 48
2 16 62 60
1 22 44 52
2 30 30 36
1 24 34 42
2 24 34 40
1 24 32 42
1 24 28 44
1 16 62 58
1 24 44 56
2  . 48 54
2 32 20 32
1 22 42 50
2 26 50 50
2 14 60 62
1 22 42 55
2 30 30 38
1 18 32 47
1 28 50 52
1 23 48  .
2 28 40 50
2 34 24 34
1 32 44 54
2 26 48 48
2 18 64 65
1 22 44 52
2 28 30 36
. 24 31 42
1 26 62 58
1 26 44 56
2 20 48 55
2 36 28 32
2 32  . 54
2 24 50 50
1 30 54 66
1 22 40 56
1 33 32 32
1 28 32 44
1 18 60 50
2 20 48 50
2 20 44 52
2 32 28 34
1 20 42 54
2 28 48 48
2 18 57 60
1 24 47 53
2 24 40 51
2 24 42 50
2 26 38 48
2 26 36 48
2 30 30 36
1 24 39 42
1 14 62 58
1 28 44 56
2  . 48 54
2 32 30 32
2 24 34 54
1 20 44 50
2 31 50 50
2 14 64 62
1 25 40 54
2 30 30 28
1 22 28 46
1 28 60 52
1 20 48  .
2 28 40 50
2 32 32 34
1 29 47 54
2 26 48 48
2 25 64 60
1 22 45 48
2 28 30 36
. 23 34 42
1 26 62 58
2 24 44 56
1 24 42 50
1 24 40 52
1 24 44 54
2 22 48 54
2 36 32 32
2 32  . 57
2 22 50 50
1 30 54 64
1 20 40 56
1 34 32 32
1 30 32 44
1 17 60 52
2 22 44 50
2 22 44 52
2 32 28 34
1 22 42 52
2 28 48 48
2 16 62 60
1 22 44 52
2 35 30 36
1 28 37 42
2 24 34 40
1 24 36 42
1 21 28 41
1 16 62 58
1 24 44 56
2  . 48 54
2 32 24 32
1 22 42 50
2 26 50 50
2 14 66 62
1 22 40 55
2 30 30 28
1 18 32 46
1 28 60 52
1 16 48  .
2 28 40 50
2 34 22 34
1 32 44 54
2 26 45 48
2 18 64 60
1 22 44 52
2 28 30 36
. 24 34 42
1 26 59 58
1 29 44 56
2 20 48 54
2 36 28 32
2 32  . 54
2 24 50 49
1 30 54 64
1 22 40 56
1 34 32 32
1 28 34 44
1 18 60 52
2 22 44 50
2 22 44 52
2 34 26 34
1 22 46 54
2 23 48 51
2 18 58 60
1 24 40 52
2 27 40 52
2 24 42 50
2 26 38 53
2 26 36 48
2 30 30 35
1 24 33 42
1 16 62 58
1 28 44 56
2  . 48 54
2 32 20 32
2 24 34 54
;
proc print;
*data selection methods;
data d2; set d1;
*odd data;
if mod(_N_,2)=1;
proc print;
data d3; set d1;
*even data;
if mod(_N_,2)=0;
proc print;
data d4; set d1;
*random half;
if uniform(0) gt .5;
proc print;
run;