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

To subset data in SAS using the data step, the where statement is used to specify the conditions that observations must meet to be included in the new data set. The correct syntax for subsetting the SASHELP.BASEBALL data set to include only players in the 'East' Division with 75 or more hits is as follows:

data bball;

set sashelp.baseball;

where Division = 'East' and nHits >= 75;

run;

This code, as shown in option D, uses the where statement with the correct logical operator and to ensure that both conditions must be true for a record to be included in the new dataset. Options A, B, and C either use incorrect syntax or logical operations that do not match the required conditions for the subset. Option A has an incorrect combination of conditions, B uses two where statements which is not valid syntax, and C incorrectly uses the or operator which would include players not in the 'East' Division or with fewer than 75 hits.

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 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.

The correct answer is B. The set statement in SAS can concatenate multiple datasets together. The AMERICAN and NATIONAL datasets appear to have the same structure and variables, so the set statement without any options will combine them into one dataset called BASEBALL. The order of the datasets in the set statement determines the order of the observations in the output dataset, and since there is no variable that needs renaming to match between the two datasets, option B is the correct answer.

References:

• SAS documentation on the set statement.

The PROC CONTENTS step in SAS is used to display metadata about a SAS dataset, including information such as the names of variables, types of variables (numeric or character), lengths of variables, and other attributes like formats, labels, and indexes. Therefore, the correct answer is:

• A) a report showing the descriptor portion of the REVENUE data set

The descriptor portion of a SAS data set contains metadata about the dataset's structure, not the actual data values or any specific information about individual variables beyond their structure and definition in the dataset. Options B, C, and D suggest details that are not part of the dataset's descriptor information as shown by PROC CONTENTS.

References: SAS 9.4 Procedures Guide: Statistical Procedures.

The step that reads the SASHELP.BASEBALL data set and creates the temporary data set CATCHERS is:

data catchers;

set sashelp.baseball;

where position='C';

run;

This DATA step creates a new data set named catchers by reading in data from sashelp.baseball and selecting only those observations where the variable position has the value 'C', which stands for catchers.

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.

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 correct syntax for creating two separate data sets based on a condition in SAS involves using a single DATA step with multiple data set names followed by a SET statement and conditional OUTPUT statements. Here's a breakdown of why option B is the correct answer:

data SUV Sedans;

set sashelp.cars;

if Type = 'SUV' then output SUV;

else if Type = 'Sedan' then output Sedans;

run;

• This option correctly uses a single DATA step to declare two data sets (SUV and Sedans). It reads from the sashelp.cars data set and uses conditional statements to output observations to the respective data sets based on the value of the Type variable. The output statement is used to explicitly direct observations to the specified data set.
• Option A: The syntax data=SUV data=Sedans; is incorrect. The correct syntax to create multiple data sets in a DATA step does not include equal signs (=).
• Option C: The syntax within the conditional statements is incorrect (if Type = SUV and if Type = Sedan). The values for Type should be enclosed in quotes to specify that they are strings.
• Option D: The syntax data= (SUV Sedans) ; is incorrect. The correct method to declare multiple data sets in a DATA step does not use parentheses or an equal sign.

References:The correctness of option B is based on standard SAS programming practices for conditional data manipulation within a DATA step. This approach is commonly documented in SAS programming resources such as the SAS 9.4 documentation and various SAS programming guides. The use of the output statement for directing data to specific datasets based on conditions is a fundamental technique in efficient data handling in SAS.

Option C is correct. The set statement is used within a DATA step to read an existing SAS data set. In this case, set sashelp.shoes; reads the SASHELP.SHOES data set, and data work.total; specifies the creation of a new data set named TOTAL in the WORK library. The options A, B, and D are incorrect because they either use the wrong syntax or are not proper statements for reading an input data set and creating an output data set.

References:

• SAS 9.4 documentation on the DATA step.

In the provided image of the SAS code for the PROC PRINT step, the following statements are present:

• proc print data=sashelp.cars; - PROC PRINT step beginning
• var Make Model MSRP MPG_City MPG_Highway Horsepower Weight; - VAR statement to specify variables to print
• format Weight comma8.; - FORMAT statement to apply a format to a variable
• The final run; statement which would be necessary to execute the PROC PRINT step is not visible in the image, but it can be inferred to be there since every PROC step must be ended with a run; or quit; statement.

Thus, there are four statements related to the PROC PRINT step.

References:

• SAS 9.4 Language Reference: Concepts, "PROC PRINT"
• SAS documentation on "VAR Statement" and "FORMAT Statement"

The report shown in the image is a two-way frequency table generated by the PROC FREQ procedure which shows the frequency and percentage distribution of two categorical variables. The correct answer is option B:

• proc freq data=cars; tells SAS to use the PROC FREQ procedure on the dataset cars.
• tables make*drivetrain; requests the frequency table for the cross of make and drivetrain. The asterisk (*) denotes a two-way table of the two categorical variables.
• run; indicates the end of the proc freq step.

The resulting table in the output has the statistics for Make broken down by Drivetrain category, which matches the structure seen in the provided image.

Options A, C, and D do not correctly request the two-way table of make by drivetrain. Specifically, C and D reverse the order, which would change the orientation of the table in the output, and A is missing the asterisk (*) which is needed for the cross-tabulation of the two variables.

References:

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

The DROP statement during the compilation phase of the DATA step flags variables in the Program Data Vector (PDV) to be dropped when the data set is output. This means that although the variables exist in the PDV during the DATA step execution, they will not be written to the output data set. The DROP statement does not affect the order of variables (which is the purpose of the ORDER= data set option), nor does it remove variables from the input data set or prevent them from being created in the PDV.

References:

• SAS documentation on the DROP statement.

In the provided program, there are six distinct SAS statements:

• data FemaleStudents; - Data step beginning
• set sashelp.Class; - Set statement
• where Sex="F"; - Where statement
• Classroom="Red Room"; - Assignment statement
• run; - Run statement to execute the data step
• title "Female Students in Red Room"; - Title statement

Note that the proc print and the second run; statement are part of another PROC step to print the results and hence are not counted in this particular count. The final title; statement is used to clear the title setting and does not count as part of the program statements being asked about.

References:

• SAS 9.4 Language Reference: Concepts, "DATA Step"
• SAS documentation on "TITLE Statement"

In SAS, the DATA step is a powerful tool that allows programmers to perform a variety of tasks such as reporting, managing, and analyzing data. The DATA step processes data one observation at a time, making it highly efficient for data manipulation tasks. It enables the creation of new datasets, modification of existing ones, and complex data transformations. Additionally, within a DATA step, you can use a wide range of programming statements and functions to calculate new variables, merge or sort datasets, and perform conditional processing. The flexibility and functionality provided by DATA steps make them a fundamental part of SAS programming for handling and preparing data for further analysis or reporting.References: SAS 9.4 Language Reference: Concepts.

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

Data set options in SAS, such as KEEP= (to specify variables to keep in a dataset) and RENAME= (to change the names of variables in a dataset), have specific rules for their usage:

• A. The options must be placed in parentheses - This is correct. When specifying dataset options in SAS, they must be enclosed in parentheses immediately following the dataset name, without any spaces in between.
• D. The options are placed after the data set name - This is also correct. Dataset options follow the dataset name and are enclosed in parentheses to modify how SAS reads or writes the dataset in that step.

Option B is incorrect because data set options are allowed in both DATA and PROC steps, provided they are relevant to the procedure being used. Option C is incorrect because data set options can be applied to both input and output datasets, depending on the context and specific operation being performed.

References: SAS 9.4 Language Reference: Concepts.

The correct syntax for the CONTENTS procedure is to specify the dataset to be described using the data= option. The dataset should be identified by its library and name, separated by a period. The correct syntax is therefore Proc contents data=library.dataset;, which makes Option C the correct answer: Proc contents data=sashelp.shoes;. This statement will produce the contents of the dataset 'shoes' in the 'sashelp' library.

References:

• SAS documentation on the CONTENTS procedure, SAS Institute.

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://documentation.sas.com/?docsetId=proc &docsetTarget=n12jw1r2n7auqqn1urrh8jwezk00.htm&docsetVersion=9.4&locale=en#:~:text=ASCENDING%20is%20the%20default%20sort%20order.&text=In%20a%20PROC%20SORT%20KEY,is%20sorted%20in%20ascending%20order.

The default sort order for PROC SORT in SAS is ascending. This means that if no other sort order is specified, SAS will arrange the data in ascending order based on the values of the variable(s) listed in the BY statement.

Here's an example:

• proc sort data=mydata; by variable; run; sorts mydata by variable in ascending order by default.

The other options are incorrect in the context of the default sort order:

• A. 'Internal' is not a sort order.
• C. 'Formatted' refers to sorting data based on formatted values, not the default order.
• D. 'Descending' is an alternative sort order that must be explicitly specified with the DESCENDING keyword.

References:

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