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

In SAS, the correct syntax for assigning labels to variables is to use the LABEL statement within a DATA step or a PROC step. Labels are assigned to variables using the format variable='label'. The correct syntax for the LABEL statement is represented by option B.

Here’s the breakdown:

• FName=’First Name’ correctly assigns the label First Name to the variable FName.
• LName=’Last Name’ correctly assigns the label Last Name to the variable LName.
• Each variable and label pair is separated by a space, and the overall statement ends with a semicolon, which is the proper syntax for a LABEL statement in SAS.

Options A, C, and D are incorrect due to various syntax errors like the use of the wrong character for the apostrophe, missing apostrophes, incorrect punctuation, and in the case of option C, an incorrect conjunction ‘and’ which is not used in LABEL statements.

References:

• SAS 9.4 documentation for the LABEL statement: SAS Help Center: LABEL Statement

In SAS, footnotes are set using the footnote statement and they will appear on all subsequent output until they are either changed or cleared. Based on the second image provided with the SAS code, the footnote for the second PROC PRINT report is set immediately before it runs.

The code sets footnote1 as 'Created by HR' and footnote2 as 'Confidential' initially. However, before the second PROC PRINT step, footnote2 is redefined as 'Draft - Do Not Distribute'. Since footnote1 is not redefined or cleared, it is no longer in effect for the second report.

Therefore, the only footnote that appears for the second PROC PRINT report is what is defined for footnote2 at that point in the code, which is 'Draft – Do Not Distribute'. That's why the correct answer is D.

References:

• SAS 9.4 documentation for the FOOTNOTE statement: SAS Help Center: FOOTNOTE Statement

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.

The PROC MEANS report shown in the image displays statistics for a single variable Age with no decimal places. The correct SAS code to generate such a report is option D, which uses the PROC MEANS procedure with the maxdec=0 option to control the number of decimal places displayed (in this case, zero) and specifies Age as the analysis variable using the var statement.

The PROC MEANS procedure computes descriptive statistics for numeric variables. The maxdec=0 option is used here to remove decimal places from the report output, which matches the output shown where the mean, standard deviation, minimum, and maximum are all integers.

The other options are incorrect for the following reasons:

• A uses the class statement, which is not appropriate here because Age is not a classification variable but an analysis variable.
• B uses the group statement, which is not a valid statement in the PROC MEANS procedure.
• C uses the by statement, which requires the data to be sorted by the BY variable and does not fit the output provided since it would produce separate statistics for each value of Age.

References:

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

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.

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

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"

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.

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 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.

In SAS program syntax, character strings are indeed case sensitive when enclosed in quotation marks. If you compare two character strings of the same letters but different cases, SAS will treat them as different values. For example, 'Hello' is not the same as 'hello'.

Option A is incorrect because the ampersand (&) is not used for comments in SAS; it is used for macro variable references. Option B is incorrect because global statements such as LIBNAME and options do not require a RUN statement to execute. Finally, option D is incorrect because SAS can process steps with multiple statements on the same line, provided that they are correctly separated by semicolons.

References

• SAS 9.4 Language Reference: Concepts, "SAS Language Elements and Syntax."

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.

When using a BY statement in a DATA step, SAS creates two temporary variables for each BY variable: FIRST.variable and LAST.variable. These are used to indicate the beginning and end of each BY group.

For Ellen's observation:

• First.State=1 because this is the first occurrence of the state "OH" in the dataset when sorted by the state variable, which makes it the beginning of a new group for "OH".
• Last.State=0 because Ellen is not the last observation

for the state "OH" group. In the given dataset snippet, there appears to be only one observation for the state "OH", but since the data is sorted by state, and we don't see another "OH" below Ellen, we can deduce that Ellen's observation is not the last "OH" observation in the entire dataset. If there were no more "OH" observations following Ellen's, then Last.State would be 1.

The FIRST.variable is set to 1 for the first observation in each BY group and 0 for all other observations in the group. Conversely, LAST.variable is set to 1 for the last observation in each BY group and 0 otherwise. Since we're assuming that the dataset is larger than the snippet shown, and the data continues beyond what is visible, we must assume there are more observations for "OH" unless indicated otherwise.

References

• "SAS 9.4 Language Reference: Concepts." SAS Institute Inc.
• "BY-Group Processing" in "SAS Programming 1: Essentials" course material, SAS Institute.

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 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 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 MEANS statement is used to compute descriptive statistics of data in SAS. Option A is the correct code to produce the report shown in the first image because of the following reasons:

• data=sashelp.shoes specifies the dataset on which the procedure is to be performed.
• sum mean specifies that the summary statistics should include the sum and mean of the variables.
• var Sales; specifies that the variable Sales is the analysis variable for which the summary statistics are to be computed.
• class Product; specifies that the procedure should classify results by unique values of the Product variable. This will produce separate statistics for each type of product, which aligns with the structure of the report provided in the image.

Options B, C, and D are incorrect for the following reasons:

• B uses group instead of class, and group is not a valid statement in the context of PROC MEANS. Also, var Sale; is incorrect as the variable name is Sales.
• C includes nobe; which is not a valid SAS option and seems to be a typo. The by statement is used for sorting data, not for classifying groups as class does.
• D incorrectly uses sum Salad; and mean Sales; as separate statements and has an invalid use of by product; which is not needed here.

References:

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

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 DATA step provided, average is calculated using the mean function, which calculates the average of the non-missing values of the variables listed. The variables provided are:

• var1 = 2
• var2 = 4
• var3 = .
• var4 = 6

The mean function in SAS ignores missing values, represented by a period (.). Hence, the average is computed using the non-missing values (2, 4, and 6). The mean of these three numbers is calculated as: (2 + 4 + 6) / 3 = 12 / 3 = 4

Therefore, the value of average is 4.

References:

• SAS documentation on the MEAN function, SAS Institute.

The correct syntax for generating the mean and standard deviation for specified variables using PROC MEANS is shown in option A. The PROC MEANS statement specifies the dataset to analyze (data=class) and includes the options (mean std) directly in the PROC statement. The VAR statement then lists the variables for which the statistics should be calculated (Height and Weight). The other options listed in B, C, and D are not correct syntax for PROC MEANS.