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.

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.

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.

The correct answer is A: Ods excel= ' c:\report.xlsx ' style=analysis;. This syntax is correct for the ODS EXCEL statement in SAS, where you specify the path and filename, followed by the ' style ' option to apply a specific style template to the output Excel file. The ' style=analysis ' is used to set the output appearance according to the ' ANALYSIS ' style template provided by SAS. Option B is syntactically incorrect and does not use the ' style ' option correctly. Option C incorrectly places a slash which is not syntactically valid in this context, and Option D misses the equals sign and quotes which are necessary for correct syntax in SAS. References:

SAS documentation on ODS EXCEL statement: SAS Support: ODS EXCEL Statement

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

The code creates two datasets, preteen and teen, based on the age variable from the sashelp.class dataset. The if statement checks each observation, and if the age is less than 13, the observation is written to the preteen dataset; otherwise, the observation is written to the teen dataset.

From the provided frequency table, we can see that there are 7 observations with ages less than 13 (2 for age 11 and 5 for age 12), so the preteen dataset will have 7 observations. Since the sashelp.class dataset has a total of 19 observations, the remaining 12 observations (19 total - 7 preteen = 12 teen) will be written to the teen dataset.

Thus, the answer is: B. preteen will have 7 observations and teen will have 12 observations.

References:

SAS documentation on the DATA step and IF-THEN/ELSE logic, SAS Institute.

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 be yond 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 PROC SORT statement that specifies the sort variable is: BY

The BY statement in PROC SORT is used to specify the variable(s) by which the data should be sorted.

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.

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]

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 "

In the given statement, BirthDate = 15DEC2005’d; , the ' d ' denotes a SAS date constant, which is a numeric value representing a specific date. SAS date values are stored as numeric variables counting the number of days from January 1, 1960. Therefore, BirthDate is a numeric variable, making option B correct. This constant does not represent a character string (eliminating A), and the byte size of any numeric variable in SAS is 8 by default, not 9 (eliminating C). There is no syntax error in the statement (eliminating D).

References:

SAS documentation on dates, times, and datetime values, SAS Institute.

The PROC PRINT statement is used for printing SAS datasets. To customize the column headers in the report, you use the label statement within the PROC PRINT procedure to assign new labels to variables, and the label option in the PROC PRINT to activate these labels. The noobs option suppresses the printing of observation numbers in the report.

Option B has the correct syntax for what is being requested:

proc print data=cities label noobs; specifies the dataset to print with the label option to display variable labels and noobs to hide the observation numbers.

label Name= ' Employee Name ' City= ' Birth City ' ; assigns the label ' Employee Name ' to the ' Name ' variable and ' Birth City ' to the ' City ' variable.

run; signifies the end of the PROC PRINT procedure.

Options A, C, and D are incorrect due to syntax errors:

A uses an incorrect option showlabelse instead of label and noobs .

C is incorrect because it lacks the label option in the proc print statement which is necessary to actually display the labels, and the labels are being incorrectly used within the proc print instead of in a label statement.

D has several issues: there is no display statement in SAS, the option noobs should be outside of the proc print statement, and the labels should be defined in a label statement, not within proc print .

References:

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

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.

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

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.

The FORMAT statement in the DATA step assigns formats to variables for the SAS dataset being created. In the code provided, MSRP is given the dollar12. format and Invoice is given the dollar10. format. However, during the PROC PRINT step, MSRP is reassigned to the comma12.2 format. The format specified in the most recent PROC step or DATA step that executes is the one that is used in the output.

Therefore, the format for MSRP in the PROC PRINT output will be comma12.2 , making the answer: B. Comma12.2

References:

SAS documentation on PROC PRINT and FORMAT 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 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.