A00-215 SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Questions and Answers

In PROC PRINT, the VAR statement is used to control the order of the variables displayed in the report. You can list the variables in the order you want them to appear. The KEEP statement can control which variables appear, but not their order. DROP and SELECT are not valid statements within PROC PRINT for controlling the order of variables.

References

• SAS documentation for PROC PRINT.

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.

In the PROC PRINT statement, the LABEL option is used to display variable labels in the report. If the variables in the dataset have labels associated with them, the LABEL option will ensure that these labels are used in the output instead of the variable names.

Here's how the LABEL option is used:

• proc print data=sashelp.class label; (assuming sashelp.class is the dataset in question)
• The LABEL keyword after the dataset name within the PROC PRINT call activates the use of variable labels in the output report.

The other options provided are incorrect for the following reasons:

• SHOWLABELS is not a valid SAS option.
• COLS does not exist as a PROC PRINT option in SAS.
• LABELS= is not a correct syntax for any SAS procedure.

References:

• SAS 9.4 documentation for the PROC PRINT statement with LABEL option: [SAS Help Center: PROC PRINT]

The correct answer is A. The SET statement in SAS is used within a DATA step to specify which existing SAS dataset is to be read. This statement is used to read in data from an existing SAS dataset to be processed in the current DATA step. The SET statement does not specify an output data set; that is determined by the name specified in the DATA statement.

Options B, C, and D are incorrect because:

• B and C are incorrect as the SET statement is not used in the PROC SORT step at all.
• D is incorrect because the SET statement specifies the input dataset, not the output dataset, in the DATA step.

References:

• SAS 9.4 Language Reference: Concepts, "DATA Step Processing"
• SAS documentation on the SET statement.

In SAS, datasets can be either temporary or permanent, depending on the library where they are stored. Temporary datasets are stored in the Work library and are deleted at the end of the session, while permanent datasets reside in user-defined libraries or in libraries that refer to a more persistent storage location.

For this question:

• B. Mylib.new: This is a permanent dataset. The prefix 'Mylib' suggests it is stored in a user-defined library (not the temporary 'Work' library), implying that the data persists beyond the current session unless explicitly deleted or if the library's link to the storage location is removed.
• D. Temp.new: Despite the potentially misleading name 'Temp', if this dataset is not explicitly stored in the Work library, it could indeed be permanent. The permanence of a dataset is determined by its library reference, not by its name. If 'Temp' is a user-defined library linked to a persistent storage, then 'Temp.new' is also permanent.

C. Work.new: This dataset is explicitly temporary as it is stored in the Work library, which is cleared at the end of the SAS session.

A. New: Without additional context about the library, 'New' does not provide enough information to determine its permanence. It could be either temporary or permanent depending on the library it references.

References:SAS documentation on libraries and dataset management, SAS Institute.

The default length of numeric variables in SAS data sets is 8 bytes.

In SAS, the default byte size of a numeric variable is 8 bytes. This allows for a significant amount of precision and a wide range of numeric values to be stored within a numeric variable, regardless of the actual number of digits in the number being stored.

References:

• SAS documentation on numeric variables, SAS Institute.

In SAS, the SUBSTR function is used to extract a substring from a character string. The function syntax is SUBSTR(string, position, length), where:

• string is the variable or string literal you want to extract the substring from.
• position is the starting position of the substring within string.
• position starts counting at 1 in SAS, not 0 as in some other languages.
• length is the number of characters to extract.

For the value of date provided ("02Apr2019"), we want to extract the year, which is the four characters at the end of the string.

Here's how each option would work given the string:

A) year=substr(date, 7, 4);This starts at the 7th character of the string ("2019") and extracts 4 characters, which correctly represents the year.

B) year=substr(date, 4, 6);This starts at the 4th character ("Apr2019") and would extract 6 characters, which gives us "Apr201", not just the year.

C) year=substr(date, 6, 4);This starts at the 6th character ("r2019") and would extract 4 characters, resulting in "r201", which is not correct.

D) year=substr(date, 4, 7);This starts at the 4th character and would extract 7 characters, resulting in "Apr2019", which is the whole string from the 4th character to the end, not just the year.

The correct answer is A, as it extracts the four-digit year from the end of the string.

References:

• The SAS documentation on the SUBSTR function, which details how to use it for extracting parts of strings.
• SAS programming tutorials that often provide examples of common functions like SUBSTR for string manipulation

In SAS, when you use a BY statement in a DATA step, SAS creates two temporary variables for each variable listed in the BY statement: one to indicate the first occurrence (FIRST.variable) and another to indicate the last occurrence (LAST.variable) of the value within the BY-group. Given the provided code and assuming that State is the variable used in the BY statement, SAS will create First.State and Last.State. Thus, option A is correct.

References:

• SAS documentation on the BY statement, SAS Institute.

The type and length of SnackType are character and 7, which makes option B correct. In the provided program, SnackType is assigned a value of "Chips" which is a character string. The length statement is used to explicitly declare SnackType as a character variable with a length of 7 before it is used, which will take precedence over any later assignments or implications about the variable's type or length.

References:

• SAS documentation on variable length.

Option B is correct. The DATE9. format in SAS displays dates in the ddMMMyyyy format, which corresponds to the example given (25JUN2019). This format writes dates with a two-digit day, a three-character month abbreviation, and a four-digit year. The other options do not match the correct format:

• A is incorrect because ddMMMyy9. format would display a two-digit year.
• C is incorrect because there is no such format as Ddmmmyyyy9. in standard SAS formats.
• D is incorrect because Dmy9. does not correspond to the required format.

References:

• SAS 9.4 documentation on date and time formats.

When defining custom formats in SAS, it's important to adhere to the correct syntax, which includes ending format names with a period. In the submitted program, the format $convert is defined without a period at the end of the format name in the VALUE statement. This is likely causing an error since format names in the VALUE statement should always end with a period. Option C correctly identifies that adding a period to the end of the format name on the VALUE statement will allow SAS to properly recognize and apply the custom format to the Answer variable when the PROC PRINT step is executed.

The program provided in the question seems to have formatting errors, but based on the information provided, the suggested change is to add a period to make it $convert. which would correctly apply the format.

The other options would not resolve the issue of applying the custom format:

• A. Changing the case of the unformatted values will not help if the format is not correctly specified.
• B. The comma does not seem to be the issue based on the context given.
• D. The dollar sign is correct and necessary for character formats; removing it would cause the format to be invalid for character data.

References:

• SAS 9.4 documentation for the FORMAT procedure: SAS Help Center: PROC FORMAT

https://v8doc.sas.com/sashtml/lrcon/z0961108.htm

In SAS, the automatic variable _N_ represents the number of times the DATA step has iterated. It starts at 1 and increments by 1 each time the DATA step loops back to the top. This variable can be used within the DATA step to monitor the iteration count but is not written to the output data set. The other options, A, C, and D, are not automatically created variables that track iterations in the DATA step.

References:

• SAS documentation on automatic variables.

Option B is the correct answer. This code will create two datasets as described. The keep= option in the data chips statement will ensure that only QtySold, Price, and Product are kept in the chips dataset, and because othersnacks does not have a keep= option, it will contain all the variables from the input dataset. The if-then-else logic directs the observations to the correct dataset based on the Type value.

Option A incorrectly uses a keep statement within the if block, which is not valid syntax. Option C attempts to use a keep statement after the output statement, which will not correctly subset the variables for the chips data set. Option D incorrectly applies the keep= option to the set statement, which would affect both output data sets, not just chips.

References:

• SAS documentation on the output statement.
• SAS documentation on subsetting data in the DATA step.

The FORCAST dataset is created from the INVEST dataset, which has 10 observations as seen in the PROC PRINT report. For each observation in INVEST, three new observations are added in FORCAST, one for each year's balance calculation (year=1, year=2, year=3). This is achieved by the output; statement after each balance calculation, which writes the current state of the data step to a new row in the dataset. Therefore, since there are 10 original observations, and each leads to three new observations, the total number of observations in the FORCAST dataset will be 30 (10 observations from INVEST multiplied by 3 years each).

References:

• SAS documentation on the DATA step and output statement, SAS Institute.

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.

The correct syntax for the LIBNAME statement in SAS, which assigns a libref to a library stored at a specific path, requires the libref to come first, followed by the path enclosed in quotes. The format is libname libref 'path';. Thus, the correct syntax among the options provided is Option B: libname mydata 'c:\sas\data';. This statement assigns the libref 'mydata' to the directory 'c:\sas\data'. The other options either invert the order of the libref and path or improperly use the equals sign, which is not standard syntax for the LIBNAME statement.

References:SAS documentation on the LIBNAME statement, SAS Institute.

SAS handles missing values distinctively based on the data type of the variable. For numeric variables, SAS represents missing values with a period (.). For character variables, missing values are represented by a blank space. This handling is crucial for distinguishing between actual data entries and absent data, particularly in statistical calculations and data processing. Options B, C, and D incorrectly describe the representation of missing values in SAS, which does not use special characters like 'N', 'C', or '$' for this purpose.

References:SAS documentation on handling missing data, SAS Institute.

The program fails because option C is correct: you must include the dataset height2 in the DATA statement. The DATA step is trying to write to a dataset named height2, which has not been defined in the DATA statement. The correct syntax to create two datasets in one DATA step is to list them both in the DATA statement like so:

data height1 height2;

The use of numbers in dataset names is not a problem in SAS, nor is outputting to different data sets within a single DATA step. Additionally, using two different DATA statements for HEIGHT1 and HEIGHT2 is not required and is not the cause of the failure.

References:

• SAS documentation on the DATA statement and creating multiple data sets.

The resulting WORK.REVENUE data set contains 3 variables. In the provided SAS program, the set statement uses a (keep=) option to keep only 3 variables from WORK.PRODUCTS, which are ProdId, Price, and Sales. The drop= data set option in the data statement specifies to drop the Sales and Returns variables from the output data set. However, Returns was not included in the keep= option, so it won't be part of WORK.REVENUE to begin with. Finally, a new variable Revenue is calculated and included in the data set. Therefore, the final data set contains the variables ProdId, Price, and Revenue.

References:

• SAS documentation on keep= and drop= data set options.

The correct syntax for creating an Excel workbook using the ODS (Output Delivery System) Excel destination with a specific style is provided by option D. The syntax is as follows: ods excel file='c:\report.xlsx' style=analysis;This statement instructs SAS to output the results of subsequent procedures to an Excel workbook located at c:\report.xlsx, applying the ANALYSIS style to the output. The file= option specifies the path and name of the Excel file to be created or overwritten, and the style= option indicates the style template to be used for the output. The ANALYSIS style is one of the predefined styles that can be applied to the output to control the appearance of tables and graphs. Other options like A) and B) are incorrect due to syntax errors and misplacement of keywords. Option C) has a typo in the file path and incorrect syntax usage.References: SAS 9.4 Output Delivery System: User's Guide.