*2.*

COMPUTE bmi=weight / (height / 100) ** 2.
EXECUTE.

COMPUTE broca= height - 100.
EXECUTE.


*3.*

RECODE age (Lowest thru 19=0) (20 thru 35=1) (36 thru 50=2) (51 thru 65=3) (66 thru Highest=4) INTO 
    age_class.
EXECUTE.

VALUE LABELS age_class 0 "<20" 1 "20-35" 2 "36-50" 3 "51-65" 4 ">65".


*4.*
*BMI*

DO IF  (gender = "male").
RECODE bmi (Lowest thru 19.99=1) (20 thru 25=2) (25.001 thru 30=3) (30.001 thru 40=4) (40.001 thru 
    Highest=5) INTO bmi_class.
END IF.
EXECUTE.

VALUE LABELS bmi_class 1 "Untergewicht" 2 "Normalgewicht" 3 "Übergewicht" 4 "Adipositas" 5 "massive Adipositas".


DO IF  (gender = "female").
RECODE bmi (Lowest thru 18.99=1) (19 thru 24=2) (24.001 thru 30=3) (30.001 thru 40=4) (40.001 thru 
    Highest=5) INTO bmi_class.
END IF.
EXECUTE.

VALUE LABELS bmi_class 1 "Untergewicht" 2 "Normalgewicht" 3 "Übergewicht" 4 "Adipositas" 5 "massive Adipositas".


*Broca*

IF  (gender = "male") broca_ideal=broca - broca * 0.10.
EXECUTE.

IF  (gender = "female") broca_ideal=broca - broca * 0.15.
EXECUTE.

IF  (gender = "male") broca_normal=broca.
EXECUTE.

IF  (gender = "female") broca_normal=broca - broca * 0.05.
EXECUTE.


*5.*

CROSSTABS
  /TABLES=gender BY bmi_class
  /FORMAT=AVALUE TABLES
  /CELLS=COUNT
  /COUNT ROUND CELL.


*6.*

CROSSTABS
  /TABLES=age_class BY bmi_class
  /FORMAT=AVALUE TABLES
  /CELLS=COUNT
  /COUNT ROUND CELL.


*7.*

FREQUENCIES VARIABLES=age height weight bmi
  /NTILES=4
  /STATISTICS=VARIANCE SEMEAN MEAN MEDIAN
  /ORDER=ANALYSIS.


*8.*

SORT CASES  BY gender.
SPLIT FILE LAYERED BY gender.

FREQUENCIES VARIABLES=weight bmi
  /STATISTICS=STDDEV MEAN
  /ORDER=ANALYSIS.


*9.*

IF  (gender = "male") bmi_normalgewicht=22.5*(height/100)**2.
EXECUTE.

IF  (gender = "female") bmi_normalgewicht=21.5*(height/100)**2.
EXECUTE.

FREQUENCIES VARIABLES=broca_normal bmi_normalgewicht
  /STATISTICS=STDDEV MEAN
  /ORDER=ANALYSIS.