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

In SAS, footnotes are set using the footnote statement and they will appear on all subsequent output until they are either changed or cleared. Based on the second image provided with the SAS code, the footnote for the second PROC PRINT report is set immediately before it runs.

The code sets footnote1 as 'Created by HR' and footnote2 as 'Confidential' initially. However, before the second PROC PRINT step, footnote2 is redefined as 'Draft - Do Not Distribute'. Since footnote1 is not redefined or cleared, it is no longer in effect for the second report.

Therefore, the only footnote that appears for the second PROC PRINT report is what is defined for footnote2 at that point in the code, which is 'Draft – Do Not Distribute'. That's why the correct answer is D.

References:

• SAS 9.4 documentation for the FOOTNOTE statement: SAS Help Center: FOOTNOTE Statement

In the DATA step provided, average is calculated using the mean function, which calculates the average of the non-missing values of the variables listed. The variables provided are:

• var1 = 2
• var2 = 4
• var3 = .
• var4 = 6

The mean function in SAS ignores missing values, represented by a period (.). Hence, the average is computed using the non-missing values (2, 4, and 6). The mean of these three numbers is calculated as: (2 + 4 + 6) / 3 = 12 / 3 = 4

Therefore, the value of average is 4.

References:

• SAS documentation on the MEAN function, SAS Institute.

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.