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

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.

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 correct statement to import a CSV file into SAS and create a dataset is option B. The PROC IMPORT statement is used in SAS to read data from external files and create a SAS data set. Let's break down why option B is correct:

• datafile= specifies the location and filename of the external data file. In this case, "sales.csv" is the correct filename and format for a CSV file.
• dbms=csv tells SAS that the format of the external data file is CSV (comma-separated values).
• out=mydata.sales; specifies the name of the output SAS dataset. It consists of two parts: the libref mydata and the dataset name sales. This tells SAS to store the new dataset in a library called mydata with the dataset name sales.

Option A uses an incorrect syntax as it incorrectly specifies the data= option, which is not valid in this context. Also, the out= option is incorrectly quoted and terminated with a semicolon within the quotes.

Option C has a typo in the out= option (out=mydata.gales;), which incorrectly specifies the output dataset name. Additionally, it incorrectly specifies the data= option, which should actually be datafile=.

Option D has incorrectly quoted the out= option and uses a hyphen instead of an equals sign. Additionally, it does not use quotes around the filename, which may cause issues if the filename contains special characters or spaces.

References:SAS 9.4 documentation, specifically the PROC IMPORT statement: SAS Help Center: PROC IMPORT Statement