This document provides sample questions and content guides for the SAS 9.4 Base Programming certification exam. The exam will test skills in accessing and managing SAS data, conditional processing, using SAS functions, and generating reports. It will include performance-based practical programming questions involving reading, sorting, and categorizing SAS data, as well as standard multiple choice questions covering topics like using SAS procedures, formats, and loops.

1. Sample Questions
The following sample questions are not inclusive and do not
necessarily represent all of the types of
questions that comprise the exams. The questions are not
designed to assess an individual's readiness to
take a certification exam.
SAS 9.4 Base Programming – Performance-based Exam
Practical Programming Questions:
Project 1:
This project will use data set sashelp.shoes.
Write a SAS program that will:
• Read sashelp.shoes as input.
• Create the SAS data set work.sortedshoes.
• Sort the sashelp.shoes data set:
o First by variable product in descending order.
o Second by variable sales in ascending order.
Run the program and answer the following questions:
Question 1: What is the value of the product variable in
observation 148?

2. Answer: Slipper
Question 2: What is the value of the Region variable in
observation 130?
Answer: Pacific
Project 2:
This project will use the data set sashelp.shoes.
Write a SAS program that will:
• Read sashelp.shoes as input.
• Create a new SAS data set, work.shoerange.
• Create a new character variable SalesRange that will be used
to categorize the observations into
three groups.
• Set the value of SalesRange to the following:
o Lower when Sales are less than $100,000.
o Middle when Sales are between $100,000 and $200,000,
inclusively.
o Upper when Sales are above $200,000.
Run the program, then use additional SAS procedures to answer
the following questions:
Question 3: How many observations are classified into the

3. “Lower” group?
Answer: 288
Question 4: What is the mean value of the Sales variable for
observations in the “Middle” group? Round
your answer to the nearest whole number.
Answer: 135127
Project 3:
This project will work with the following program:
data work.lowchol work.highchol;
set sashelp.heart;
if cholesterol lt 200 output work.lowchol;
if cholesterol ge 200 output work.highchol;
if cholesterol is missing output work.misschol;
run;
This program is intended to:
• Divide the observations of sashelp.heart into three data sets,
work.highchol, work.lowchol, and
work.misschol

4. • Only observations with cholesterol below 200 should be in the
work.lowchol data set.
• Only Observations with cholesterol that is 200 and above
should be in the work.highchol data
set.
• Observations with missing cholesterol values should only be
in the work.misschol data set.
Fix the errors in the above program. There may be multiple
errors in the program. Errors may be syntax
errors, program structure errors, or logic errors. In the case of
logic errors, the program may not
produce an error in the log.
After fixing all of the errors in the program, answer the
following questions:
Question 5: How many observations are in the work.highchol
data set?
Answer: 3652
Question 6: How many observations are in the work.lowchol
data set?
Answer: 1405
Standard Questions:

5. Question 7:
The following SAS program is submitted:
data WORK.TEMP;
Char1='0123456789';
Char2=substr(Char1,3,4);
run;
What is the value of Char2?
A. 23
B. 34
C. 345
D. 2345
Answer: D
Question 8:
The following SAS program is submitted:
proc format;
value score 1 - 50 = 'Fail'

6. 51 - 100 = 'Pass';
run;
Which one of the following PRINT procedure steps correctly
applies the format?
A. proc print data = SASUSER.CLASS;
var test;
format test score;
run;
B. proc print data = SASUSER.CLASS;
var test;
format test score.;
run;
C. proc print data = SASUSER.CLASS format = score;
var test;
run;
D. proc print data = SASUSER.CLASS format = score.;
var test;
run;
Answer: B

7. Question 9:
Given the SAS data set WORK.ONE:
Revenue2008 Revenue2009 Revenue2010
----------- ----------- -----------
1.2 1.6 2.0
The following SAS program is submitted:
data WORK.TWO;
set WORK.ONE;
Total=sum(of Rev:);
run;
What value will SAS assign to Total?
A) 3
B) 1.6
C) 4.8

8. D) The program fails to execute due to errors.
Answer: C
Question 10:
Given the SAS data set WORK.INPUT:
Var1 Var2
------ -------
A one
A two
B three
C four
A five
The following SAS program is submitted:
data WORK.ONE WORK.TWO;
set WORK.INPUT;
if Var1='A' then output WORK.ONE;
output;
run;

9. How many observations will be in data set WORK.ONE?
Enter your numeric answer in the space below.
Answer: 8
Major Project 1 (MP1)
Personal Nursing Philosophy
Your Personal Philosophy must address and have the following
Topics Headings:
Topic
Description
Key Concepts (20 pts.)
Explain the key concepts of your philosophy/theory.
Metaparadigms
(20 pts.)
Describe the four (4) Metaparadigms of nursing as you view
them and how they apply in your own practice area.
Nursing Process - Philosophy
(15 pts.)
Express how your philosophy could be applied to your present
nursing practice, research, administration and/or education.
Nursing Process – Strengths & Limitations
(15 pts.)
Elaborate on your philosophy’s strength and limitations.
Original Work
(10 pts.)
Paper must be your original work.
Paper Format
(10 pts.)
Paper should be no more than four (4) pages long, double space
and typed in Microsoft WORD file.

10. APA Style
(10 pts.)
Paper should adhere to APA style (includes introduction, body,
conclusion) with correct grammar spelling are expected.
NUR3846 | Foundation of Professional Nursing
Exam Content Guide
1
SAS 9.4 Base Programming – Performance Based Exam
Access and Create Data Structures
Create temporary and permanent SAS data sets.
• Use a DATA step to create a SAS data set from an existing
SAS data set.
Investigate SAS data libraries using base SAS utility
procedures.
• Use a LIBNAME statement to assign a library reference name
to a SAS library.
• Investigate a library programmatically using the CONTENTS
procedure.
Access data.

11. • Access SAS data sets with the SET statement.
• Use PROC IMPORT to access non-SAS data sources.
o Read delimited and Microsoft Excel (.xlsx) files with PROC
IMPORT.
o Use PROC IMPORT statement options (OUT=, DBMS=,
REPLACE)
o Use the GUESSINGROWS statement
• Use the SAS/ACCESS XLSX engine to read a Microsoft Excel
workbook.xlsx file.
Combine SAS data sets.
• Concatenate data sets.
• Merge data sets one-to-one.
• Merge data sets one-to-many.
Create and manipulate SAS date values.
• Explain how SAS stores date and time values.
• Use SAS informats to read common date and time expressions.
• Use SAS date and time formats to specify how the values are
displayed.
Control which observations and variables in a SAS data set are
processed and
output.
• Use the WHERE statement in the DATA step to select
observations to be processed.
• Subset variables to be output by using the DROP and KEEP
statements.
• Use the DROP= and KEEP= data set options to specify
columns to be processed and/or

12. output.
Manage Data
Exam Content Guide
2
Sort observations in a SAS data set.
• Use the SORT Procedure to re-order observations in place or
output to a new dataset
with the OUT= option.
• Remove duplicate observations with the SORT Procedure.
Conditionally execute SAS statements.
• Use IF-THEN/ELSE statements to process data conditionally.
• Use DO and END statements to execute multiple statements
conditionally.
Use assignment statements in the DATA step.
• Create new variables and assign a value.
• Assign a new value to an existing variable.
• Assign the value of an expression to a variable.
• Assign a constant date value to a variable.
Modify variable attributes using options and statements in the
DATA step.

13. • Change the names of variables by using the RENAME= data
set option.
• Use LABEL and FORMAT statements to modify attributes in a
DATA step.
• Define the length of a variable using the LENGTH statement.
Accumulate sub-totals and totals using DATA step statements.
• Use the BY statement to aggregate by subgroups.
• Use first. and last. processing to identify where groups begin
and end.
• Use the RETAIN and SUM statements.
Use SAS functions to manipulate character data, numeric data,
and SAS date
values.
• Use SAS functions such as SCAN, SUBSTR, TRIM, UPCASE,
and LOWCASE to perform
tasks such as the tasks shown below.
o Replace the contents of a character value.
o Trim trailing blanks from a character value.
o Search a character value and extract a portion of the value.
o Convert a character value to upper or lowercase.
• Use SAS numeric functions such as SUM, MEAN, RAND,
SMALLEST, LARGEST, ROUND,
and INT.
• Create SAS date values by using the functions MDY, TODAY,
DATE, and TIME.
• Extract the month, year, and interval from a SAS date value by
using the functions

14. YEAR, QTR, MONTH, and DAY.
• Perform calculations with date and datetime values and time
intervals by using the
functions INTCK, INTNX, DATDIF and YRDIF.
Exam Content Guide
3
Use SAS functions to convert character data to numeric and vice
versa.
• Explain the automatic conversion that SAS uses to convert
values between data types.
• Use the INPUT function to explicitly convert character data
values to numeric values.
• Use the PUT function to explicitly convert numeric data
values to character values.
Process data using DO LOOPS.
• Explain how iterative DO loops function.
• Use DO loops to eliminate redundant code and to perform
repetitive calculations.
• Use conditional DO loops.
• Use nested DO loops.
Restructure SAS data sets with PROC TRANSPOSE.
• Select variables to transpose with the VAR statement.
• Rename transposed variables with the ID statement.

15. • Process data within groups using the BY statement.
• Use PROC TRANSPOSE options (OUT=, PREFIX= and
NAME=).
Use macro variables to simplify program maintenance.
• Create macro variables with the %LET statement
• Use macro variables within SAS programs.
Error Handling
Identify and resolve programming logic errors.
• Use the PUTLOG Statement in the Data Step to help identify
logic errors.
• Use PUTLOG to write the value of a variable, formatted
values, or to write values of all
variables.
• Use PUTLOG with Conditional logic.
• Use temporary variables N and ERROR to debug a DATA
step.
Recognize and correct syntax errors.
• Identify the characteristics of SAS statements.
• Define SAS syntax rules including the typical types of syntax
errors such as misspelled
keywords, unmatched quotation marks, missing semicolons, and
invalid options.
• Use the log to help diagnose syntax errors in a given program.

16. Exam Content Guide
4
Generate Reports and Output
Generate list reports using the PRINT procedure.
• Modify the default behavior of PROC PRINT by adding
statements and options such as
o use the VAR statement to select and order variables.
o calculate totals with a SUM statement.
o select observations with a WHERE statement.
o use the ID statement to identify observations.
o use the BY statement to process groups.
Generate summary reports and frequency tables using base SAS
procedures.
• Produce one-way and two-way frequency tables with the
FREQ procedure.
• Enhance frequency tables with options (NLEVELS, ORDER=).
• Use PROC FREQ to validate data in a SAS data set.
• Calculate summary statistics and multilevel summaries using
the MEANS procedure
• Enhance summary tables with options.
• Identify extreme and missing values with the UNIVARIATE
procedure.
Enhance reports system user-defined formats, titles, footnotes
and SAS System
reporting options.

17. • Use PROC FORMAT to define custom formats.
o VALUE statement
o CNTLIN= option
• Use the LABEL statement to define descriptive column
headings.
• Control the use of column headings with the LABEL and
SPLIT=options in PROC PRINT
output.
Generate reports using ODS statements.
• Identify the Output Delivery System destinations.
• Create HTML, PDF, RTF, and files with ODS statements.
• Use the STYLE=option to specify a style template.
• Create files that can be viewed in Microsoft Excel.
Export data
• Create a simple raw data file by using the EXPORT procedure
as an alternative to the
DATA step.
• Export data to Microsoft Excel using the SAS/ACCESS XLSX
engine.
Note: All 23 main objectives will be tested on every exam. The
70 expanded objectives are
provided for additional explanation and define the entire
domain that could be tested.
Sheet1ObjectiveDetailsAccess and Create Data StructuresCreate
temporary and permanent SAS data sets.- Use a DATA step to

18. create a SAS data set from an existing SAS data set.Investigate
SAS data libraries using base SAS utility procedures.- Use a
LIBNAME statement to assign a library reference name to a
SAS library.- Investigate a library programmatically using the
CONTENTS procedure.Access data.- Access SAS data sets with
the SET statement.- Use PROC IMPORT to access non-SAS
data sources.Read delimited and Microsoft Excel (.xlsx) files
with PROC IMPORT.Use PROC IMPORT statement options
(OUT=, DBMS=, REPLACE)Use the GUESSINGROWS
statement- Use the SAS/ACCESS XLSX engine to read a
Microsoft Excel workbook.xlsx file.Combine SAS data sets.-
Concatenate data sets.- Merge data sets one-to-one.- Merge data
sets one-to-many.Create and manipulate SAS date values.-
Explain how SAS stores date and time values.- Use SAS
informats to read common date and time expressions.- Use SAS
date and time formats to specify how the values are
displayed.Control which observations and variables in a SAS
data set are processed and output.- Use the WHERE statement
in the DATA step to select observations to be processed.-
Subset variables to be output by using the DROP and KEEP
statements.- Use the DROP= and KEEP= data set options to
specify columns to be processed and/or output.Manage DataSort
observations in a SAS data set.- Use the SORT Procedure to re-
order observations in place or output to a new dataset.- Remove
duplicate observations with the SORT Procedure.Conditionally
execute SAS statements.- Use IF-THEN/ELSE statements to
process data conditionally.- Use DO and END statements to
execute multiple statements conditionally.Use assignment
statements in the DATA step.- Create new variables and assign
a value.- Assign a new value to an existing variable.- Assign the
value of an expression to a variable.- Assign a constant date
value to a variable.Modify variable attributes using options and
statements in the DATA step.- Change the names of variables
by using the RENAME= data set option.- Use LABEL and
FORMAT statements to modify attributes in a DATA step.-
Define the length of a variable using the LENGTH

19. statement.Accumulate sub-totals and totals using DATA step
statements.- Use the BY statement to aggregate by subgroups.-
User first. and last. processing to identify where groups begin
and end.- Use the RETAIN and SUM statements.Use SAS
functions to manipulate character data, numeric data, and SAS
date values.- Use SAS functions such as SCAN, SUBSTR,
TRIM, UPCASE, and LOWCASE to perform tasks such as the
tasks shown below.Replace the contents of a character
value.Trim trailing blanks from a character value.Search a
character value and extract a portion of the value.Convert a
character value to upper or lowercase.- Use SAS arithmetic,
financial, and probability functions to create or modify numeric
values by using the INT and ROUND functions.- Create SAS
date values by using the functions MDY, TODAY, DATE, and
TIME.- Extract the month, year, and interval from a SAS date
value by using the functions YEAR, QTR, MONTH, and DAY.-
Perform calculations with date and datetime values and time
intervals by using the functions INTCK, INTNX, DATDIF and
YRDIF.Use SAS functions to convert character data to numeric
and vice versa.- Explain the automatic conversion that SAS uses
to convert values between data types.- Use the INPUT function
to explicitly convert character data values to numeric
values.Process data using DO LOOPS.- Explain how iterative
DO loops function.- Use DO loops to eliminate redundant code
and to perform repetitive calculations.- Use conditional DO
loops.- Use nested DO loops.Restructure SAS data sets with
PROC TRANSPOSE.- Select variables to transpose with the
VAR statement.- Rename transposed variables with the ID
statement.- Process data within groups using the BY statement.-
Use PROC TRANSPOSE options (OUT=, PREFIX= and
NAME=).Use macro variables to simplify program
maintenance.- Create macro variables with the %LET statement-
Use macro variables within SAS programs.Error
HandlingIdentify and resolve programming logic errors.- Use
the PUTLOG Statement in the Data Step to help identify logic
errors.- Use PUTLOG to write the value of a variable, formatted

20. values, or to write values of all variables.- Use PUTLOG with
Conditional logic.- Use temporary variables N and ERROR to
debug a DATA step.Recognize and correct syntax errors.-
Identify the characteristics of SAS statements.- Define SAS
syntax rules including the typical types of syntax errors such as
misspelled keywords, unmatched quotation marks, missing
semicolons, and invalid options.- Use the log to help diagnose
syntax errors in a given program.Generate Reports and
OutputGenerate list reports using the PRINT procedure.-
Modify the default behavior of PROC PRINT by adding
statements and options such asuse the VAR statement to select
and order variables.calculate totals with a SUM statement.select
observations with a WHERE statement.use the ID statement to
identify observations.use the BY statement to process
groups.Generate summary reports and frequency tables using
base SAS procedures.- Produce one-way and two-way frequency
tables with the FREQ procedure.- Enhance frequency tables
with options (NLEVELS, ORDER=).- Use PROC FREQ to
validate data in a SAS data set.- Calculate summary statistics
and multilevel summaries using the MEANS procedure-
Enhance summary tables with options.- Identify extreme and
missing values with the UNIVARIATE procedure.Enhance
reports system user-defined formats, titles, footnotes and SAS
System- Use PROC FORMAT to define custom
formats.reporting options.VALUE statementCNTLIN= option-
Use the LABEL statement to define descriptive column
headings.- Control the use of column headings with the LABEL
and SPLIT=options in Proc Print output.Generate reports using
ODS statements.- Identify the Output Delivery System
destinations.- Create HTML, PDF, RTF, and files with ODS
statements.- Use the STYLE=option to specify a style template.-
Create files that can be viewed in Microsoft Excel.Export data-
Create a simple raw data file by using the EXPORT procedure
as an alternative to the DATA step.- Export data to Microsoft
Excel using the SAS/ACCESS XLSX engine.