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SAS - A00 231 SAS 9.4 Programming Perfomance Based Exam

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SAS 9.4 Base Programming - Performance-Based Exam Overview', '

Overview of SAS 9.4 Base Programming Exam

The SAS 9.4 Base Programming - Performance-Based Exam is designed to test your proficiency in SAS programming fundamentals. This comprehensive exam focuses on a range of critical skills and knowledge necessary for effective data handling and analysis.

Exam Composition

  • Access and Create Data Structures: 20-25%
  • Manage Data: 35-40%
  • Error Handling: 15-20%
  • Generate Reports and Output: 15-20%

Registration and Exam Details

Register for the exam with Exam ID: A00-231 through SAS and Pearson VUE. Ensure you are familiar with the system requirements for online proctoring available on the SAS website to avoid any issues during the exam session.

Preparation Tips

Review the comprehensive exam content guide, understand all topics in-depth, and engage in hands-on practice to excel. Remember, no external resources are allowed, and managing your time effectively during the exam is crucial.

Target Audience for SAS 9.4 Base Programming Exam', '

Target Audience for SAS 9.4 Base Programming Exam

The SAS 9.4 Base Programming exam is specifically designed for professionals looking to establish or enhance their credentials as SAS Base programmers. It is ideal for those who are involved in writing SAS programs to access, manage, and analyze data to produce reports.

This exam is best suited for:

  • Data Analysts
  • Statistical Analysts
  • Data Scientists who use SAS
  • Business Analysts interested in quantitative analysis
  • Aspiring SAS Programmers

Candidates should have experience in data management and manipulation, the creation of reports, and the use of SAS data step programming. A solid foundation in basic programming concepts and tasks specific to the SAS environment is recommended before attempting the exam.

  • 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:
    • 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 DELIMITER 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 and IF statements 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.

  • 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:
    • 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 for various tasks.
    • 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 YEAR, QTR, MONTH, and DAY.
    • Perform calculations with date and datetime values and time intervals by using the functions INTCK, INTNX, 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.
    • 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.
    • 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.
    • Use the macro variable name dot delimiter (.)

  • 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.

  • Generate list reports using the PRINT procedure:
    • Modify the default behavior of PROC PRINT by adding statements and options such as:
      • Use 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.
      • Use the NOOBS and LABEL options.
  • 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:
      • WAYS, CLASS, VAR, OUTPUT statements
    • Enhance summary tables with options.
    • Identify extreme and missing values with the UNIVARIATE procedure.
  • Enhance reports using user-defined formats, titles, footnotes, and SAS System reporting options:
    • Use PROC FORMAT to define custom formats:
      • VALUE statement
      • 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, XLSX, and PPTX files with ODS statements.
    • Use the STYLE=option to specify a style template.
    • Generate comma separated value (CSV) files with ODS statements.
  • Export data:
    • Create a simple raw data file by using the EXPORT procedure as an alternative to the DATA step:
      • Control the export file format with common DBMS identifiers: (csv, jmp, tab, dlm).
    • Export data to Microsoft Excel using the SAS/ACCESS XLSX engine.
Frequently Asked Questions

The exam tests data access and creation, data management, error handling, and report generation. Download the complete exam content guide for more information.

The exam consists of 20-25% on data access and creation, 35-40% on data management, and 15-20% each on error handling and report generation.

There are 40-45 multiple choice and short-answer questions.

The exam lasts 135 minutes and the passing score is 725 out of a possible 1,000 points.

The exam fee is $180 in the US and most other countries.

No external resources are allowed during the exam.

Review the exam content guide thoroughly, understand all the topics, and make sure you can create a SAS library using a LIBNAME statement. Hands-on practice is crucial.

Source data sets are write-protected to prevent data corruption. Save edited data in a different location as explained within the exam.

Stay organized by saving each program before moving to the next. Keep an eye on the clock and don't spend too much time on projects that aren't working.

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