Free Practice Questions for SAS Institute A00-215 Exam

To rename a variable when reading a dataset in SAS, you use the rename= option inside the parentheses following the dataset's name in the set statement. The correct syntax for renaming the variable 'Name' to 'StudentName' is: rename=(oldname=newname). Therefore, the correct option is A, which correctly places the old variable name 'Name' first, followed by an equal sign, and then the new variable name 'StudentName'. The parentheses enclose the rename operation, and it is correctly nested within the set statement.

References:

SAS documentation on the RENAME= data set option, SAS Institute.

In SAS, the FORMAT procedure (PROC FORMAT) allows users to create custom formats that can be used to change the way data is displayed without altering the data itself. The VALUE statement within PROC FORMAT is a key component of this procedure.

The VALUE statement can indeed create both numeric and character formats, which is why option C is correct. Numeric format names typically do not start with a $ sign (this is reserved for character format names), and the keyword UNKNOWN is not a part of the VALUE statement syntax; it is used in a different context within PROC FORMAT, specifically for handling undefined data values when using custom formats.

Moreover, the LIB= option is not used within the VALUE statement. The LIB= option is used at the PROC FORMAT level to specify the library where the formats should be stored or from which they should be read.

References

SAS 9.4 documentation for the PROC FORMAT and VALUE statement.

"SAS Formats and Informats." in "Step-by-Step Programming with Base SAS 9.4" from the SAS Institute.

In the provided code snippet, Line 3 contains a syntax error. The keep statement is used incorrectly here; the correct keyword to use is where in order to filter the dataset. The correct line should be something like:

where Make = 'Honda';

So, the keep statement on Line 3 is not properly used, and also there appears to be a missing quotation mark at the end of 'Honda' which should be closed before the semicolon.

References:

SAS documentation for the where statement.

The correct answer is option D, which uses the LIBNAME statement correctly to assign a library reference to an Excel workbook and specifies the correct syntax for accessing a worksheet within that workbook. The syntax for this option is:

libname exlib xlsx "c:\class.xlsx";

proc print data=exlib.class_test;

run;

This code snippet assigns the library reference exlib to the Excel workbook located at c:\class.xlsx using the XLSX engine. The PROC PRINT step is then used to display the contents of the worksheet named CLASS_TEST within that workbook. The library reference exlib combined with the dataset name class_test (following the .) correctly specifies the worksheet to be printed. The other options (A, B, C) are incorrect due to various reasons: incorrect syntax for the LIBNAME statement, incorrect specification of the dataset to be printed, and incorrect path specifications.References: SAS 9.4 Guide to Software Updates.

In SAS, character variables are indeed capable of holding alphabetic characters, numeric digits, and other special characters, which makes Option A the correct answer. This flexibility allows for storing a wide range of data as text, including combinations that may include symbols and numbers typically found in addresses, identification codes, or textual data that includes special characters. Unlike numeric variables, character variables do not interpret the data as numbers but as literal strings of characters. Options B, C, and D contain inaccuracies regarding how data types and values are treated in SAS. Specifically, numeric values in SAS are never enclosed in quotes (which contradicts B), character variables can exceed 200 bytes depending on the specific declaration (contradicting C), and while numeric variables can indeed include numbers, decimal points, minus signs, and scientific notation, they do not typically include currency symbols as part of the variable's numeric value (contradicting D).

References:SAS documentation on data types, 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.

The correct answer is D. This option uses the PROC PRINT procedure, which is used to print SAS data sets. The format statement within PROC PRINT temporarily assigns a format to a variable for the duration of the PROC PRINT step. Here is how it works:

data=sashelp.shoes; tells SAS which dataset to print.

Format sales comma12.; temporarily assigns a comma format to the sales variable, making it easier to read, especially if the numbers are large. The comma12. format adds commas for thousands, millions, etc., and displays the number in a field that is 12 characters wide.

The format is only applied for the duration of the PROC PRINT step and does not permanently change the dataset.

The other options are incorrect for the following reasons:

Option A attempts to use a PROC FORMAT step, which is for creating custom formats, not for assigning formats to variables in a dataset.

Option B uses a DATA step which could permanently assign the format to the sales variable if it were syntactically correct (it should be set sashelp.shoes; instead of Set sashelp,sheoes;).

Option C mentions PROC CONTENTS which displays metadata about variables in a dataset and does not have the capability to assign formats.

References:

SAS 9.4 documentation for the PROC PRINT statement: SAS Help Center: PROC PRINT

The correct answer is C. The DATA step and PROC PRINT steps ran without errors. In the SAS log shown, there is a clear error in the PROC SORT step because of the use of an incorrect option by ascending Increase which caused the "Variable ASCENDING not found" error. However, the DATA step completed successfully, as indicated by the "NOTE" that follows it, confirming that 56 observations were read from the SASHELP.SHOES data set where Region is Africa. Additionally, the PROC PRINT step also completed successfully, indicated by the "NOTE" at the bottom of the log which confirms that 56 observations were read from the WORK.AFRICA data set, implying the PROC PRINT step executed without issue.

A is incorrect because the error in PROC SORT did not cause the program to stop; SAS continued processing the next steps. B is incorrect because the PROC SORT step did not run successfully. D is incorrect because the PROC PRINT step did not fail; it ran successfully.

References:

SAS documentation on error messages.

Understanding the SAS log and error messages.

In SAS, the code you provided involves creating two datasets, table1 and table2, from the dataset sashelp.shoes. The key part to understand here is how the DATA statement and OUTPUT statement interact with the specified datasets.

DATA Statement: The statement data table1 table2; initiates the creation of two new datasets named table1 and table2.

SET Statement: The set sashelp.shoes; statement is used to read data from the sashelp.shoes dataset. This dataset includes data on shoe sales from SASHELP library, which is commonly used for demonstration purposes in SAS.

OUTPUT Statement: In the context of the DATA step where multiple datasets are specified in the DATA statement (as in table1 table2), the OUTPUT statement without a dataset name specified outputs the current observation to all datasets listed in the DATA statement. This is a critical point because it determines where the data goes after processing in the DATA step.

Execution: When the run; statement is executed, it processes each observation from sashelp.shoes. For each observation, because there is no condition or additional OUTPUT statements specifying dataset names, each observation is output to both table1 and table2.

Therefore, the correct behavior as described is that each observation in sashelp.shoes is written to both table1 and table2. This effectively duplicates each row from the source into both target datasets.

References:

SAS 9.4 Language Reference: Concepts, "DATA Step Processing" and "OUTPUT Statement" sections provide detailed explanations on how DATA steps process and how OUTPUT statement works in different contexts.

Practical examples and explanations from SAS programming courses and official SAS documentation, which discuss DATA and SET statements, and their interaction with OUTPUT in data duplication scenarios.