A00-420 無料問題集「SASInstitute SAS Viya Intermediate Programming」

（A）CASPROC

（B）CASKMEANS

（C）CASSTAT

（D）CASCLUSTER

（A）simple.numRows results=x/
table={caslib="casuser", name="cars"};
print "Table casuser.cars has " x[numrows] "rows.";

（B）simple.numRows result=x/
table={caslib="casuser", name="cars"};
print "Table casuser.cars has " x.numrows "rows.";

（C）simple.numRows results=x/
table={caslib="casuser", name="cars"};
print "Table casuser.cars has " numrows[x] "rows.";

（D）simple.numRows result=x/
table={caslib="casuser", name="cars"};
print "Table casuser.cars has " numrows.x "rows.";

（A）cas.merge

（B）cas.combine

（C）cas.link

（D）cas.join

（A）source myCode;
"data OutData;
set casuser.cars;
where ""make = 'Honda'"";
run;"
endsource;

（B）source myCode;
data OutData;
set casuser.cars;
where make = 'Honda';
run;
endsource;

（C）source myCode;
"data OutData;" ||
"set casuser.cars;" ||
"where make = 'Honda';" ||
"run;"
endsource;

（D）source myCode;
"data OutData;
set casuser.cars;
where make = 'Honda';
run;"
endsource;

（A）ORDER BY

（B）SORT DSN

（C）PROC SORT

（D）SORT DESCENDING

（A）Enhanced modeling techniques

（B）Better visualization capabilities

（C）Faster processing of large datasets

（D）Easier data preparation

（A）select Species, SepalWidth, SepalLength
from casuser.iris
where Species ^= "Setosa"
;

（B）select HouseID, Brand, exp(logPrice) as Price
from casuser.margarin
where calculated Price > 5
;

（C）create table work.age12 as
select Name, Height, Weight
from casuser.class
where age=12
;

（D）create table casuser.incomplete as
select AgeAtStart, Height, cholesterol, Chol_Status
from casuser.heart
where cholesterol is null
;

（A）ALTER TABLE

（B）LOAD

（C）EXPORT

（D）APPEND

（A）PROC GLM

（B）PROC SQL

（C）PROC FREQ

（D）PROC MEANS

（A）CASTATS

（B）CASUTIL

（C）CASDESCRIBE

（D）CASMEANS

（A）cas.calculate

（B）cas.generate

（C）cas.transform

（D）cas.derive

（A）Using the FORMAT statement in the DATA step

（B）Using the BY statement in PROC FORMAT

（C）Using the LABEL statement in PROC FORMAT

（D）Using the WHERE statement in PROC SQL

（A）R

（B）SAS

（C）Python

（D）Java

（A）cas.covariance

（B）cas.relationship

（C）cas.association

（D）cas.correlation

（A）cas.tabulate

（B）cas.crosstab

（C）cas.pivot

（D）cas.summary

（A）data casuser.employees;
set work.employees;
by department;
totcomp = sum(salary,bonus);
run;

（B）data casuser.employees /single=yes;
set casuser.employees;
totcomp = sum(salary,bonus);
run;

（C）data casuser.employees /single=yes;
set work.employees;
totcomp = sum(salary,bonus);
run;

（D）data casuser.employees;
set casuser.employees;
by department;
totcomp = sum(salary,bonus);
run;

（A）MERGE statement

（B）SET statement

（C）PROC SQL

（D）OUTPUT statement

（A）CASPROC

（B）CASANALYZE

（C）CASFACTOR

（D）CASSCORE