A00-215 Exam Dumps : SAS Certified Associate: Programming Fundamentals Using SAS 9.4

In SAS, the PROC SORT procedure is used to sort data. To save the sorted data into a new dataset, the OUT= option is used in the PROC SORT statement. This option allows you to specify the name of the output dataset that will contain the sorted data.

Here is how it's used:

• proc sort data=original out=sorted; by variable; run; will sort the dataset original by variable and create a new dataset named sorted containing the sorted data.

Option A, Data=, is not valid for the PROC SORT procedure. Option B, SORTOUT=, is a common misconception but is not correct; OUT= is the right option. Option C, OUTPUT=, is not used within PROC SORT; it is used in other procedures such as PROC TABULATE and PROC SUMMARY for output datasets.

References:

• SAS 9.4 documentation for the PROC SORT statement: SAS Help Center: PROC SORT

In the provided DATA step, the merge statement is used to combine the PATIENT and VISIT data sets by the variable Id. The number of observations in the resulting ALLVISITS data set will equal the number of unique Id values that appear in both the PATIENT and VISIT data sets, because the merge in SAS is a one-to-one merge by default when the by statement is used without additional options like in=.

Looking at the provided data sets, each Id in the PATIENT data set has corresponding entries in the VISIT data set. Since there are 5 unique Id values and the VISIT data set contains multiple observations for some Id values (specifically, Id 2 and 5 have more than one visit), the ALLVISITS data set will have a total of 7 observations (1 for each patient plus the additional visits for Id 2 and 5).

References:

• SAS documentation on the merge statement.

The report shown is a cross-tabulation of 'Region' by 'Product'. The FREQ Procedure indicates that PROC FREQ has been used, and the presence of 'Frequency', 'Percent', 'Row Percent', and 'Column Percent' suggests that a cross tabulation (or contingency table) has been requested. The correct code for this output would include the tables statement to specify the two variables ('Region' and 'Product') with an asterisk between them, which indicates a request for a cross-tabulation of these two categorical variables, and the crosslist option to display the table in a cross-tabulated list format. Therefore, option D is the correct answer:

proc freq data=sashelp.shoes;

tables region*product / crosslist;

run;

Options A and C use the order=freq option incorrectly, as this option would order the table by frequency counts rather than providing a cross-tabulation. Option B is missing the crosslist option needed to produce the cross-tabulated format.