The Top SAS Interview Questions You Need to Know

Interviewing for a job using SAS? You’ll want to master these commonly asked SAS interview questions.

SAS (Statistical Analysis System) is an integrated software suite that enables users to perform a variety of analytics, business intelligence, and data management tasks. SAS is used by organizations across many industries such as finance pharmaceuticals, telecom, retail and more.

As a result, SAS skills are in high demand. If you want to get a good job or move up as a SAS developer, programmer, or analyst, you need to do well on the technical interview.

This article will cover:

• An overview of SAS
• The most frequently asked SAS interview questions and answers
• Tips for preparing for your SAS interview

Let’s get started!

SAS is a well-known brand of advanced analytics software that has been around since 1976. The SAS system is comprised of various software suites:

• SAS Base: Core features needed to write SAS programs. Includes data management, statistical procedures, report writing.

• SAS Statistical: Tools for advanced statistical analysis like regression, psychometric analysis, multivariate analysis, survey data analysis, etc.

• SAS Enterprise Guide: GUI-based SAS environment for data queries, reporting, and analytics. Allows coding in SAS or via point and click interface.

• SAS Enterprise Miner: GUI data mining interface for developing predictive models using techniques like neural networks, regression, decision trees, etc.

Some key capabilities of SAS include:

• Data management – data cleansing, preparation, reporting, ETL
• Statistical analysis – descriptive, predictive, prescriptive
• Business intelligence and analytics
• Data visualization – graphs, charts, plots
• Forecasting and predictions using machine learning
• Text analytics and text mining

SAS uses SAS proprietary programming language for coding. The code is written in SAS files that have .sas extension.

Overall, SAS allows users to easily analyze big data using advanced analytics techniques. Organizations use it to uncover insights, drive strategic decision making, and improve business performance.

Now let’s look at some common SAS interview questions and answers.

Frequently Asked SAS Interview Questions and Answers

Here are some of the most frequently asked SAS interview questions for both freshers and experienced candidates:

SAS Programming Interview Questions

Q1: Explain the SAS database?

SAS uses a SAS database known as SAS Files. SAS files are stored in SAS libraries which are folders containing multiple SAS files.

There are 2 types of SAS files:

• SAS Data Set: Contains actual data values as well as metadata like variable names, variable types, number of observations, etc.

• SAS Program: Contains SAS code or syntax written using SAS proprietary language.

Q2: What are the different DATA Step statements in SAS?

The major DATA Step statements are:

• INPUT – Reads data values from source into SAS dataset
• DATALINES – Denotes the start of data values
• SET – Reads an existing SAS dataset
• MERGE – Combines multiple SAS datasets into one
• INFILE – Reads data from external files into SAS
• PROC SORT – Sorts SAS dataset
• BY – Groups SAS dataset by one or more variables

Q3: What is a LIBNAME statement?

LIBNAME statement assigns a library reference name to a physical folder location on your hard drive where multiple SAS files are stored.

LIBNAME mylibrary 'C:SAS Files';

This assigns mylibrary as library name to the physical folder C:SAS Files.

Q4: What are the different ways to subset a SAS dataset?

The different ways are:

• WHERE statement in DATA step
• IF statement in PROC step
• BY group processing
• BY variable in DATA statement
• KEEP= / DROP= data set options
• OBS= dataset option
• FIRSTOBS= / OBS= data set options

Q5: What is the difference between WHERE vs IF statement?

• WHERE limits rows selected from an input dataset
• IF limits rows processed after rows have been selected from the input dataset

So WHERE is used in DATA step, IF is used in PROC step.

Q6: What is index in SAS?

Index is a file that contains the physical location of each row in a SAS dataset. It helps SAS optimize execution time while accessing observations in a SAS dataset.

SAS Analytics Interview Questions

Q7: How can you transform variables in SAS?

SAS provides ways to transform variables:

• IF-THEN/ELSE logic in DATA step
• Arithmetic calculations and expressions
• SAS functions like LOG, SQRT, RANUNI, ROUND, etc.
• Formats to present variable values differently
• CASE statement to categorize based on conditions

Q8: What is SAS Enterprise Guide?

SAS Enterprise Guide provides a GUI for SAS programming. It allows you to access data, develop queries, and create reports via an interface instead of coding.

Key capabilities include:

• SAS code editor for writing SAS programs
• Tasks and wizards for code-free analytics
• Basic reporting and descriptive analytics
• Data exploration and visualization
• Integrated with other SAS products like Enterprise Miner

Q9: How can you summarize data in SAS?

Following methods can be used to summarize data:

• PROC MEANS – provides data summarization and descriptive stats
• PROC UNIVARIATE – provides summary stats, graphs, tests for distribution
• PROC FREQ – provides frequency tables and cross tabs
• PROC REPORT – summarizes data in a report format
• PROC TABULATE – provides custom table summaries with stats

Q10: What is SAS Macros? What are the benefits?

SAS Macro is a programming tool that provides an interface to SAS for customization and automation.

Benefits include:

• Parameterization for passing values into macros
• Improved code reusability since macros can be called multiple times
• Reduced coding time as macros can be shared across teams
• Better maintainability as any update to macro reflects everywhere
• Modularization for break code into reusable chunks

SAS Interview Questions for Experienced Candidates

Q11: Explain SAS ARRAY and how it is useful?

ARRAY creates temporary variables referred to by a shorthand name and index.

It is useful because:

• It reduces number of lines needed to write a code logic
• Makes code compact and faster to write
• Easy to modify code logic by changing array definition
• Easy to perform iterative computations by traversing through array elements

Q12: What are the different components of Base SAS Software?

Components of Base SAS include:

• Data Management: LIBNAME, FORMAT, INFORMAT, SET, MERGE, PROC SORT, BY group processing

• Reporting and Descriptive Analysis: PRINT, REPORT, MEANS, UNIVARIATE, FREQ, TABULATE procedures

• Statistical Analysis: REG, GLM, MIXED, GENMOD procedures

• Utility Programs: OPTIONS, IMPORT/EXPORT wizards

• Macro Programming: SAS Macro language

• ODS: Output delivery system for dynamic report generation

Q13: What is SAS FORMCHAR option and how does it help to create customized reports?

SAS FORMCHAR option can be used within PROC REPORT step to customize the look and feel of reports.

Some ways FORMCHAR can be used:

• Spacing between columns or rows
• Underline or emphasize text, values
• Add separators or dividers
• Change display of missing numeric values
• Change page breaks

This allows extensive customization of reports programmatically that would otherwise need manual work in Excel/Word.

Q14: Explain the steps to perform linear regression modeling in SAS?

The steps are:

1. Input raw data set
2. Treat missing values
3. Transform variables as needed using IF-THEN, SAS functions, etc.
4. Partition into training and validation data sets
5. Run PROC REG with variables, model statement, CLPARM to check fit
6. Output key indicators like R-sq, Parameter Estimates table, Prediction plot
7. Validate model by applying on validation data set
8. Repeat steps by changing independent variables or transformations

Q15: How can you improve model performance in SAS?

Ways to improve model performance:

• Try different combinations of independent variables
• Transform variables using LOG, SQRT etc.
• Interact variables using product terms
• Change model type – linear, quadratic, polynomial
• Use CLASS and GLM approach for categorical variables
• Adjust model assumptions using WEIGHT statement
• Remove outliers and leverage points
• Split continuous variables into intervals
• Increase sample by additional data collection

This allows you to iterate and improve predictive modeling.

Tips to Crack the SAS Interview

Here are some tips to help you successfully pass your SAS interview:

• Study SAS fundamentals like data steps, data management, basic stats
• Master commonly used procedures including REPORT