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Must-Read: Top 32 SAS Interview Questions & Answers

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SAS is a programming language that is very capable of data triangulation and what makes it different from other languages is its easiness to code. When going for an interview, you might be asked some tricky interview questions and if you are not very sound, it might be difficult to handle such questions. Let’s prepare for SAS Interview Questions. 

You need have knowledge of the various SAS interview questions that could be asked if you intend looking for a job. If you are just fresh out of college, then having a good know the different base SAS interview questions for freshers too.

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Top SAS Interview Questions & Answers

Below are some basic SAS Interview questions and answers that could help anybody training for SAS so as to get a broad knowledge of what to expect in such interviews:

Q 1: What is SAS and what are its functions?

Ans: This question is a simple SAS interview question for freshers and the answers are thus:

SAS means Statistical Analysis Systems and it is an integrated setoff software products. It functions is as follows:

  1. Writing reports and graphics
  2. Data management and retrieval of information
  3. Warehousing of data
  4. Project management and operation research
  5. Data mining, statistical analysis, and econometrics
  6. Forecasting, decision support, and business planning
  7. Application Improvement
  8. Quality Improvement

Q 2: List the basic structure of SAS programming.

Ans: This is another SAS freshers interview questions and the answer is:

  1. Log window
  2. Explorer window
  3. Program Editor

    SAS Interview Questions Source: Intellipaat

                               Base SAS Interview Questions

Q 3: What is data step known to be?

Ans: Data step produces an SAS dataset carrying the data along with what is known as “data dictionary.” This data dictionary has the information about different variable and their properties.

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Q 4: What are the basic elements needed to run an SAS program successfully?


  • The end of every line must have a semi-colon 
  • Input statement
  • A data statement which defines the data set
  • A run statement
  • There must be a minimum of one space between each statement or word

Q 5: What data types does SAS contain?

Ans: Numeric and Character.

Q 6: Explain the difference between nodupkey and nodup option.

Ans: Nodup compares all variables in a dataset while Nodupkey compares only the BY variables. 

Q 7: How can you debug and test your SAS program?

Ans: This can be done by using Obs=0 and systems options in order to trace the program execution in log.

Q 8: Which statement does not perform automatic conversions in comparisons?

Ans: The “where” statement in SAS performs no automatic conversions in comparisons.

Q 9: What validation tools are used in SAS?

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SAS Job Interview Questions and Answers

Ans: For Macros, options: mprint mlogig symbolgen while for DataSet: Data set name/debug Data set: Name/stmtchk.

Q 10: Explain what SAS informats are.

Ans: SAS Informats are used for reading or inputting data from external files called Flate Files ASCII files, text files or sequential files. The informat tells SAS how to read data into SAS variables.

Q 11: Describe what PROC and PROC print contents are used for.

Ans: PROC contents display the information about an SAS dataset while PROC print is to ensure that the data is correctly read into the SAS dataset.

Q 12: What is the use of Proc summary?

Ans: Proc summary is used for computing descriptive statistics on numeric variables in the SAS dataset.

Q 13: What role does Proc glm perform?

Ans: Proc glm performs simple and multiple regressions, ANOVAL (analysis of variance), analysis of covariance, multivariate analysis of variance and repeated measure analysis of variance.

Q 14: Explain the functions of PROC in SAS.

Ans: PROC steps are used for analyzing and processing data in the form of SAS dataset. It also controls a library of routines used in performing tasks on SAS data set like summarizing, sorting and listing.

Q 15: What is the function of PROC gplot?

Ans: PROC gplot can be used for creating more colorful and fanciful graphics. It also has other options.

Q 16: What are the categories in which SAS Informats are placed?

Ans: They are placed in three categories:

  • Date/Time Informats: INFORMAT w.
  • Numeric Informats: INFORMAT w.d
  • Character Informats: $INFORMATw

Q 17: What is the function of CATX syntax?

Ans: CATX SYNTAX is used to concentrate on character strings removing trailing and leading inserts and blanks separators.

Q 18: What does an SAS data consist of?

Ans: An SAS data set consists of A data portion and a descriptor portion. 

Q 19: Name some of the key concepts of SAS:

Ans: The key concepts include:

  • Missing values
  • SORT procedure
  • Log
  • IN= dataset option
  • FORMAT procedure for creating value formats
  • Data step logic
  • KEEP=, DROP=dataset options

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Q 20: What is the difference between INFILE and INPUT?

Ans: INPUT statement is used for describing variable while INFILE statement is used for identifying an external file.

In answering SAS questions; you need to understand as many programming terms as possible. The SAS questions and answers written here are sufficient for anyone who intends to have a thorough training in SAS programming language.

Q 21: Define factor analysis.

Factor analysis is a term used for a group of statistical techniques that are associated with a reduction of a set of observable variables in terms of a little number of latent factors. The major goal is for summarization and reduction of data.

Q 22: Differentiate between INFORMAT and FORMAT.

Ans: INFORMAT is used to indicate SAS that a number must be read in a certain format while FORMAT is used to indicate SAS on how the variables are printed.

Q 23: What is the difference between SUM function and ‘+’ operator?

Ans: SUM function returns the sum of arguments that are non-missing while ‘+’ operator returns a missing value in case any arguments are missing.

Q 24: Under what circumstances would you code a SELECT construct instead of IF statements?

Ans: If you have a long series of mutually exclusive conditions and they have a numeric comparison, making use of the SELECT group is more efficient than using the IF statements because the CPU time is reduced.

Q 25: Explain DATA_NULL_

Ans: DATA_NULL_ can be used for creating macro variables. It is also used to write output without making a dataset. The concept “null” is what we use as a data step that does not really create a data set.

Q 26: What is Program Data Vector (PDV)?

Ans: PDV is known to be a logical area in the memory. It is created after the creation of an input buffer. This is when SAS creates a dataset at one observation at a time, where the input buffer is created during the time of compilation, through an external file from a held record.

Q 27: Differentiate between WHERE and IF statement.


  • WHERE is used as a data set option while IF can’t be used.
  • WHERE statement can be used during subset data procedures while IF can’t be used in such procedures.
  • WHERE statement can’t be used when reading data that uses INPUT statement but IF statements can be used for such.
  • For the use of newly created variable, IF statements are utilized since it does not require variables to be present in the READIN data set.
  • WHERE statement is more efficient, compared to IF statement. It tells the SAS not to read every observation from the data set.
  • Multiple IF statements are used for executing multiple conditional statements

Q 28: Differentiate between FUNCTION and PROC.

Ans: The mean function can be said to be the average value of several variables in an observation. This average is calculated for a PROC, which is the sum of all the values of a variable divided by the observations in the variable.

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Q 29: Compare SAS, SPSS, and STATA.

SAS Job Interview Questions

SAS Interview Questions

Each of these packages has their own strengths and weaknesses, however, they for a set of tools that can be used for several varieties of statistical analysis. With the aid of Stat/Transfer, is simple converting data files from one package to the other in just a split second. This means that there are benefits in switching from one analysis package to the other depending on your problem’s nature. For instance, if you are using mixed models to perform analysis, you might want to use SAS but if you are dealing with logic regression then STATA would be the best option. On the other hand, if you are running analysis on variance then you might just make use of SPSS. If you are performing statistical analysis very frequently, then it is advisable to have each of these packages in one’s toolkit for data analysis.

Q 30: Mention the uses of SAS.

Ans: SAS software provides tools for various applications in academia, business, and government. The major uses of SAS procedures are forecasting, economic analysis, financial and economic modeling, financial reporting, time series analysis and time series data manipulation.

The normal theme relating the several applications of the software is the time series data. SAS software is useful for predicting and analyzing processes that take place over time or for analyzing models involving simultaneous relationships.

Although, SAS software is mainly associated with business, economics, and finances; time series data can arise in other areas too. The software can be useful when simultaneous relationships, time dependencies or even dynamic processes make data analysis complex. 

Q 31: How can SAS dataset with compressed observations be compressed?

Ans: In creating compressed SAS data set, use COPRESS=YES option as an output DATA set option or in an OPTION statement. If you compress a data set, its size reduces by a reduction in repeated consecutive characters or numbers to either 2-byte or 3-byte representations. If you want to uncompress observations, a DATA step must be used to copy the data set then the option COMPRESS=NO is used for the new data set.

The benefits of using the SAS compressed data set are a reduction in storage requirements for a data set and lesser I/O operations needed to be read from and written to the data set during processing. Its demerits are not being able to make use of SAS observation number to access an observation. The CPU time needed for preparing compressed observations is increased because of the overhead of compressing and expanding the observations.

Q 32: How can the space requirement for the huge data set in SAS be minimized?

Ans: Amongst several questions, this is one of the crucial SAS interview questions and answers for experienced candidates, so you must answer it very cautiously.

Whenever you work with large data sets, you can employ the following steps to decrease the space requirements:

  • Split large dataset in smaller ones
  • Clean your working space in each step as much as possible
  • Use data set options (drop=, keep=) or statement (keep, drop) for limiting to only the variables required
  • Use IF statements or OBS= to limit the number of observations
  • Use WHERE= or WHERE or index for optimizing the WHERE expression for limiting the number of observations in a PROC step or Data step.
  • Use length to limit the bytes of the variables
  • Use _NULL_ data set name whenever you don’t have to create a data set
  • Compress data set using system options or data set options.
  • Use SQL to merge, summarize, sort, etc. instead of a combination of Data step or Proc Step with temporary data sets.

Having a broad knowledge on SAS Interview questions would be very useful before going for an interview. If you are looking to know more about it, the SAS interview questions and answers are written above would be of great use.

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