A SAS program to detect outliers using IQR (interquartile range)

outlier_iqr.sas

/* Caluculate quartiles to get limits */
proc univariate data=work.ZaehlstelleZeit_&num. noprint;
  var AnzFahrzeuge;
  output out=work.ZaehlstelleStat_&num. p25=q1 p75=q3;
run;

data work.ZaehlstelleStat_&num.;
  set work.ZaehlstelleStat_#
  ZSID = "&name";
  iqr = q3 - q1;
  iqr_factor = 3; /* iqr_factor 1.5 is used for "mild" outliers, 3 for extreme outlier */
  q3_limit = q3 + (iqr * iqr_factor);
  q1_limit = q1 - (iqr * iqr_factor);
  drop iqr iqr_factor q1 q3;
run;

/* Merge dataset with statistics */
data work.ZaehlstelleZeit_&num.;
    merge work.ZaehlstelleZeit_&num. work.ZaehlstelleStat_&num.;
  by ZSID;

  MessungStatus='Messwert';
  format MessungStatus $20.;

  if missing(AnzFahrzeuge) then do;
    MessungStatus='Fehlend';
  end;
  else if AnzFahrzeuge > q3_limit OR AnzFahrzeuge < q1_limit then do;
    MessungStatus='Suspekt';
  end;
  drop q3_limit q1_limit
run;

/* Get rid of stat table */
proc datasets library=work nolist;
   delete ZaehlstelleStat_&num.;
quit;