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SAS(BASE,ADVANCED)

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  • SAS(BASE,ADVANCED)

SAS(BASE,ADVANCED)

3600 Learners
Jan 22 onwards
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SAS (BASE, ADVANCED)

SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 80,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world

SAS, (pronounced “sass”) once stood for “Statistical Analysis System,”

But now it is only SAS.

SAS began at North Carolina State University as a project to analyze agricultural research. Founded in 1976 to help all sort of customers.

SAS is both software and company.

The world biggest private sector company.

SAS giving operations in various sectors like,

Automotive

Communications

Education

Banking/Financial Services

Government

Health Insurance

Health Care Providers

Hospitality & Entertainment

Insurance

Life Sciences

Manufacturing

Media

Oil & Gas

Retail

Hotels

Utilities

And giving solution lines as

Analytics

Business Intelligence

Customer Intelligence

Data Integration & ETL

Financial Intelligence

Foundation Tools

Fraud Management

Governance, Risk & Compliance

High-Performance Computing

Human Capital Intelligence

IT Management

On Demand Solutions

Performance Management

Risk Management

Supply Chain Intelligence

Sustainability Management

 

In 1966, there was no SAS.

But there was a need for a computerized statistics program to analyze vast amounts of agricultural data collected through

United States Department of Agriculture (USDA) grants.

Then research started by University Statisticians Southern Experiment Stations, Eight land-grant universities that received the majority of their research funding from the USDA. And some schools came together under a grant from the National Institutes of Health (NIH) to develop a general-purpose statistical software package to analyze all the agricultural data they were generating.

North Carolina State University, located in the capital city of Raleigh, North Carolina became the leader in the consortium.

North Carolina State University faculty members

Jim Goodnight and Jim Barr

Emerged as the project leaders –

Barr creating the architecture and

Goodnight implementing the features

 

In 1972 NIH stopped to give funds to this team, then the consortium agreed to chip in $5,000 apiece each year to allow NCSU to continue developing and maintaining the system and supporting their statistical analysis needs.

During the coming years, SAS software was licensed by pharmaceutical companies, insurance companies and banks, as well as by the academic community that had given birth to the project.

Jane Helwig, another Statistics Department employee at NCSU, Joined the project consortium as documentation writer

John Sall, a graduate student and programmer, rounded out the core team.

Incorporation

In 1976 Goodnight, Barr, Helwig and Sall left NCSU and formed

SAS Institute Inc. – a private company “devoted to the maintenance and further development of SAS.” They opened offices in a building #2806 Hillsborough Street, across from the university.

By 1980, the growing company building capacity is not sufficient in Hillsborough Street building, and then it’s moved to the site of its present headquarters offices just outside Raleigh in Cary, North Carolina. In that time employs were 20.

In this time SAS was growing, the entire computer hardware and software industry was changing, with new operating systems and platforms placing new demands on software developers one of the first steps for SAS was to adapt the software to operate on IBM’s Disk Operating System (DOS).

Now it is working on different operating systems like windows, Dos, Z/OS, UNIX and various UNIX flavors.

In 1990 SAS Company grow with employ force of 7000.

SAS celebrated its 25th anniversary in 2001,

Its turn out from various difficulties along with the millennium and the Y2K frenzy. And they created new logo and tagline presently which we are seeing Tagline is –

THE POWER TO KNOW®

SAS has been named one of FORTUNE magazine’s “100 Best Companies to Work For” every year since 1998 and no1 in 2010

SAS named the best company to work for in 2010 by FORTUNE.

user

SRINIVAS

FACULTY NAME: SRINIVAS

EDUCATION:MS

EXPERIANCE: 8+ YEARS OF WORK AND TEACHING IN SAS

SAS CERTIFIED CANDIDATE: BASE, ADVANCE AND CLINICAL SAS

SAS (BASE, ADVANCED)

 

SAS Base & Advance Course Content – Around 200 HOURS      

WHAT IS SAS and BASICS of SAS- 12HOURS

  • History Of Sas
  • Functionality Of Sas
  • Architecture Of Sas
  • Sas Program Rules
  • File Elements Of Sas
  • Sas Names & Rule
  • Missing Data
  • Types Of Variables
  • How Sas System Read Values Into Variables
  • Lengths of Variables
  • Sas Windowing Environment
  • Sas Program & Components Of Sas Program
  • Creation Of Libraries
  • Member Types
  • Datasets
  • Views
  • Catalogs
  • Indexes
  • Sas Programming (Briefly)
  • Data Step
  • Proc Step
  • Global Options
  • Global Statements
  • Backend Process Of SAS Program
  • Installation Process
  • ETL Concepts

 

BEGIN WITH DATASTEP - 10 HOURS

  • Data Step & Purpose of Data Step
  • Data Statement & Dataset Options
  • Infile Statement & Options
  • Input Statement & Types of Input & Options
  • Datalines / Cards Statement (or) Datalines4 / Cards4 Statement
  • Run Statement / Quit Statement

 

ATTRIBUTES OF VARIABLES - 8 HOURS

  • Data Types
  • Label Statement
  • Length Statement
  • Informat Statement
  • Format Statement
  • How Dates Works In Sas
  • System Defined / User Defined Informats & Formats

 

OTHER SAS STATEMENTS - 5 HOURS

  • Keep Statement
  • Drop Statement
  • Rename Statement
  • Replace Statement
  • Sum Statement
  • Retain Statement
  • Goto Statement
  • Link Statement
  • Return Statement
  • Output Statement
  • Stop Statement

 

CONDITIONAL STATEMENTS - 4 HOURS

  • If Statement
  • If Then Statement
  • If Then Else Statement
  • If Then Delete Statement
  • If Then Remove Statement
  • If Then Output Statement
  • If Then Do Statement
  • If Then Do While Statement
  • If Then Do Until Statement
  • If Then Goto Statement
  • Where Statement
  • Operators
  • Arithmetic Operators
  • Comparison Operators
  • Logical Operators
  • Expressions

 

LOOPS - 5 HOURS

  • Do Statement
  • Do Iterative Statement
  • Do While Statement
  • Do Until Statement
  • End Statement
  • Output Statement
  • Stop Statement

 

ARRAY – 5 HOURS

  • Why Do We Need Arrays?
  • Basic Array Concepts
  • Array Statement
  • Array References
  • Variable Name Array Reference
  • Using Array Indexes
  • One Dimension Arrays&Multi-Dimension Arrays
  • Temporary Arrays
  • Sorting Arrays
  • Determining Array Bounds: Lbound And Hbound Functions
  • When To Use Arrays
  • Common Errors And Misunderstandings
  • Invalid Index Range
  • Function Name As An Array Name
  • Array Referenced In Multiple Data Steps, But Defined In Only One

 

BY - GROUP PROCESSING – 4 HOURS

  • Definitions For By-Group Processing
  • By-Group Processing
  • Sorting Data (Proc Sort)
  • By Value&By Group
  • First.Variable And Last.Variable
  • Modifying Sas Data Sets: Examples.
  • Invoking By-Group Processing
  • Preprocessing Input Data For By-Group Processing
  • Sorting Observations For By-Group Processing
  • Indexing For By-Group Processing
  • How The Data Step Identifies By Groups
  • Processing Observations In A By Group
  • How Sas Determines First.Variable And Last.Variable
  • Processing By-Groups In The Data Step
  • Processing By-Groups Conditionally
  • Data Not In Alphabetic Or Numeric Order
  • Data Grouped By Formatted Values

 

COMBINING SAS DATA SETS - 10 HOURS

  • Concatenation
  • Interleaving
  • Merge
  • Update
  • Modify

 

FUNCTIONS (100 + Functions) - 10 HOURS

  • Character / String Functions
  • Numeric Functions
  • Date Functions

 

REVIEW OF DATASTEP - 2 HOURS

 

 

SAS - PROCEDURES (PROC STEP) – 1 HOUR

  • What Is Proc Step
  • Purpose Of Proc Step
  • Types of Procedures

 

DATA ACCESS PROCEDURES - 4 HOURS

  • Sql Pass Thru Query (Proc Sql)
  • Proc Access
  • Proc Dbload
  • Libname Facility
  • Proc Import
  • Proc Export

 

 UTILITY PROCEDURES - 15 HOURS

  • Proc Contents
  • Proc Setinit
  • Proc Options
  • Proc Pwencode
  • Proc Copy
  • Proc Delete
  • Proc Printto
  • Proc Sort
  • Proc Compare
  • Proc Append
  • Proc Datasets
  • Proc Format
  • Proc Rank
  • Proc Transpose
  • Proc Template
  • Proc Forms
  • Proc Catalog
  • Proc Cport
  • Proc Cimport
  • Proc Upload
  • Proc Download
  • Proc Migrate

 

STATISTICS &STATISTICAL PROCEDURES - 15 HOURS

  • Proc Means
  • Proc Summary
  • Proc Univariate
  • Proc Freq
  • Proc Corr
  • Proc Reg
  • Proc Anova
  • Proc Glm
  • Proc Lifetest
  • Proc Lifereg
  • Proc Logistics
  • Proc Npar1way
  • Proc Ttest

 

REPORTING PROCEDURES - 10 HOURS

  • Proc Print
  • Proc Tabulate
  • Proc Report
  • Data Step Reporting (_Null_ Reporting)

 

GRAPHICAL PROCEDURES - 5 HOURS

  • Proc Gchart
  • Proc Gplot
  • Proc Sgplot
  • Proc Gis
  • Proc Gmap

 

REVIEW OF PROCSTEP - 2 HOURS

 

 

ODS (OUTPUT DELIVERY SYSTM) - 5 HOURS

  • Definition & Purpose of ODS/
  • Reports into Html, Rtf, Pdf, Excel, Csv, Ps, Xml, Markup, Css, Pcl, Output & Listing.
  • Ods File Formatting Options
  • General Ods Statements
  • Excel  XP Tagsets
  • The MSOffice2K_x Tagset Adds Options to the MSOffice2K Tagset
  • Exporting an XML Document Using a Customized Tagset
  • CSV Tagsets

 

SAS DDE (Dynamic Data Exchange) – 2 Hours

  • Introduction of DDE
  • DDE Preliminaries
  • Starting Up Excel
  • Loading and Saving a Workbook
  • Inserting SAS Data
  • Formatting of Excel Worksheet Cells
  • Insert an Excel Macro Sheet
  • Rename a Worksheet
  • Get Existing Sheet Names

 

DICTIONARY TABLES - 2 HOURS

  • What is Dictionary Tables?
  • Purpose of Dictionary Tables?
  • Vallopt, Vcatalog, Vcformat, Vchkcon, Vcolumn, Vdctnry, Vdest, Vengine, Vfilter,
  • Vformat, Vfunc, Vgopt, Vindex, Vinfomp, Vlibnam, Vlocale, Vmacro, Vmember, Voption,
  • Vsaccess, Vscatlg, Vslib, Vstable, Vstyle, Vsview, Vtable, Vtitle and Vview etc...

 

LIST OF GLOBAL STATEMENTS - 3 HOURS

  • X
  • Dm
  • Libname
  • Filename
  • Legend
  • Symbol
  • Title
  • Footnote
  • Ods

 

 

LIST OF GLOBAL OPTIONS - 5 HOURS

  • Date/Nodate
  • Number/Nonumber
  • Orientation
  • Missing
  • LS (Line Size)
  • PS (Page Size)
  • Year cut off
  • Sysprint
  • Sysin
  • User
  • Font
  • Validvarname
  • Formchar
  • Byline
  • Compress
  • Caps/Nocaps
  • Source/Nosource
  • Notes/Nonotes
  • Repalce/Noreplace
  • Firstobs
  • Obs
  • Buffno
  • Buffsize
  • Fmtsearch
  • Macro
  • Mstored
  • SASMstore
  • SASAutos
  • Merror/NoMerror
  • Serror/NoSerror
  • Mprint/NoMprint
  • Mlogic/NoMlogic
  • Symbolgen/NoSymbolgen

 

PROC SQL – 20 HOURS

INTRODUCTION TO THE SQL PROCEDURE

  • What Is Sql?
  • What Is The Sql Procedure?
  • Terminology
  • Comparing Proc Sql With The Sas Data Step

 

RETRIEVING DATA FROM A SINGLE TABLE

  • Overview Of The Select Statement
  • Selecting Columns In A Table
  • Creating New Columns
  • Sorting Data
  • Retrieving Rows That Satisfy A Condition
  • Summarizing Data
  • Grouping Data
  • Filtering Grouped Data
  • Validating A Query

 

RETRIEVING DATA FROM MULTIPLE TABLES

  • Introduction
  • Selecting Data From More Than One Table By Using Joins
  • Using Sub queries To Select Data
  • When To Use Joins And Sub queries
  • Combining Queries With Set Operators

 

 

CREATING AND UPDATING TABLES AND VIEWS

  • Introduction
  • Creating Tables
  • Inserting Rows Into Tables
  • Updating Data Values In A Table
  • Deleting Rows
  • Altering Columns
  • Creating An Index
  • Deleting A Table
  • Using Sql Procedure Tables In Sas Software
  • Creating And Using Integrity Constraints In A Table
  • Creating And Using Proc Sql Views

 

PROGRAMMING WITH THE SQL PROCEDURE

  • Introduction
  • Using Proc Sql Options To Create And Debug Queries
  • Improving Query Performance
  • Accessing Sas System Information Using Dictionary Tables
  • Using Proc Sql With The Sas Macro Facility
  • Formatting Proc Sql Output Using The Report Procedure
  • Accessing A Dbms With Sas/Access Software
  • Using The Output Delivery System (Ods) With Proc Sql

 

PRACTICAL PROBLEM-SOLVING WITH PROC SQL

  • Computing A Weighted Average
  • Comparing Tables
  • Overlaying Missing Data Values
  • Computing Percentages Within Subtotals
  • Counting Duplicate Rows In A Table
  • Expanding Hierarchical Data In A Table
  • Summarizing Data In Multiple Columns
  • Creating A Summary Report
  • Creating A Customized Sort Order
  • Conditionally Updating A Table
  • Updating A Table With Values From Another Table
  • Creating And Using Macro Variables
  • Using Proc Sql Tables In Other Sas Procedures

 

 

SAS/MACROS - 20 HOURS

  • Introduction To The Macro Facility
  • Purpose Of The Macro Facility
  • Macro Program Flow
  • How To Create Macros
  • Session Compiled Macros
  • Autocall Macros
  • Macro Variables
  • Introduction To Macro Variables
  • Automatic Macro Variables
  • User-Defined Macro Variables
  • Delimiting Macro Variable Names
  • Deleting Macro Variables
  • Macro Functions
  • Macro Mask Functions
  • Macro Definitions
  • Defining And Calling A Macro
  • Macro Parameters
  • Macro Storage
  • Data Step And Sql Interfaces-
  • Creating Macro Variables In The Data Step
  • Indirect References To Macro Variables
  • Retrieving Macro Variables In The Data Step
  • Creating Macro Variables In Sql
  • Macro Programs
  • Conditional Processing
  • Parameter Validation
  • Iterative Processing
  • Global And Local Symbol Tables
  • Framework For Developing Macro Applications
  • Debugging And Troubleshooting
  • Generating Custom Messages
  • Creating Efficient Macros
  • Review Of Macros

 

PERFORMANCE TUNING CONCEPTS - 2 HOURS

  • Cpu Time
  • Data Storage
  • I/0
  • Memory
  • Programming Time

 

TESTING & DEBUGGING TECHNIQUES - 2 HOURS

  • Data Step Debugging
  • Macro Debugging
  • Debugging Options

 

ERROR HANDLING - 2 HOURS

  • Syntax Errors
  • Logical Errors
  • Semantic Errors

 

FEATURES BETWEEN SAS VERSIONS V9 - 2 HOURS

  • 9.1
  • 9.1.2
  • 9.1.3
  • 9.2
  • 9.3
  • 9.4

 

SAS WITH UNIX/LINUX ENVIRONMENT - 10 HOURS

  • Getting Started with SAS in UNIX Environments
  • Starting SAS Sessions in UNIX Environments
  • Running SAS in a Foreground or Background Process
  • Selecting a Method of Running SAS in UNIX Environments
  • SAS Windowing Environment in UNIX Environments
  • Interactive Line Mode in UNIX Environments
  • Batch Mode in UNIX Environments
  • Running SAS on a Remote Host in UNIX Environments
  • X Command Line Options
  • Executing Operating System Commands from Your SAS Session
  • Customizing Your SAS Registry Files
  • Customizing Your SAS Session by Using System Options
  • Customizing Your SAS Session by Using Configuration and Autoexec Files
  • Defining Environment Variables in UNIX Environments
  • Determining the Completion Status of a SAS Job in UNIX Environments
  • Exiting or Interrupting Your SAS Session in UNIX Environments
  • Ending a Process That Is Running as a SAS Server
  • Ending a SAS Process on a Relational Database

 

CERTIFICATION CLASSES - 10 HOURS

  • Base Sas Certification
  • Adv Sas Certification

 

 

SAS EG (Enterprise Guide) - 10 HOURS

  • Getting Started with SAS Enterprise Guide
  • Creating Reports
  • Working with Data in the Query Builder
  • Joining Two Data Files Together
  • SAS Enterprise Guide Basics
  • Bringing Data into a Project
  • Working with Tasks
  • Producing Complex Reports in Summary Tables
  • Modifying Data Using the Query Builder
  • Sorting and Filtering Data
  • Combining Data Tables
  • Basic Statistical Analysis

 

PROJECTS

  • BFSI (Banking, Finance, Insurance/Healthcare) – 30HOURS
  • CLINICAL – 60HOURS (Along with CDISC)

 

FREE CLASSES

Along with SAS U will get Free classes which helps to make you more Understanding to get good & quick job.

  • Operating System ( Windows, Unix & Linux ) – 30 Hours
  • Database (Oracle Sql) – 30 HOURS
  • MS-Excel (Basics, Adv, Macros, Vba, Analytics & MIS) – 60 Hours
  • Statistics  - 30 Hours
  • Communication, Personality Development, Aptitude & Reasoning – 30 Hours

 

ELIGIBILITY:

Clinical / Life science /Healthcare Domain

  • B.Sc (B.Z.C, Chemistry, Biotech, Microbiology, Bio chemistry, Nutrition, Statistics)
  • M.Sc (Clinical research, Biotech, Microbiology, Zoology, Botony, Chemistry, Statistics)
  • PHARMACY (B.Pharmacy, D.Pharmacy, M.Pharmacy),
  • Medical (BDS, BHMS, BAMS, MBBS),
  • B.E/B.Tech (Biotech, Bio Informatics, Computer Science).

Banking/Finance/Healthcare/Retail & Telecom Domain     

(Any graduate/ post graduate is eligible)

  • B.Sc, B.A, B.COM, CA, BBA, BBM, BCA, B.Tech, B.E
  • M.Sc, M.A, M.COM, MBA, MCA, PGDM, M.Tech

 

For any queries please contact STANSYS

  • Mobile: 9542195422
  • Whatsapp: 9542195422
  • Phone: 040-48524449
  • Mail id: stansys.sas@gmail.com
  • Face Book: stansyssoftwresolutions@gmail.com
  • Website: www.stansys.in
  • Address: #7-1-621/113(67/3RT), Near S.R Nagar Community Hall,

Between Apollo Clinic & Nagarjuna High School,

Sanjeevareddy Nagar, Hyderabad- 500038, Telangana.

 

 


  1. - -

    -


Q #1) Enlist the functions performed by SAS.

Answer: SAS (Statistical Analysis System) has its own importance in every business domain.

Enlisted below are some of the summarized functions that are performed by SAS:

  • Data Management and Project Management
  • Data Warehousing
  • Operational Research and decisional support
  • Information Retrieval and Quality Management
  • Business Planning
  • Statistical Analysis

Q #2) What are the 3 components in SAS programming?

Answer: The 3 components in SAS programming are:

  • Statements
  • Variables
  • Dataset

Q #3) Enlist the syntax rules followed in SAS statements.

Answer: SAS program is written in Editor Window. Here, it contains a series of statements followed by the proper syntax in an order for the SAS program to understand it.

Some of the syntax rules that are followed in the case of Statement component of SAS are as follows:

  • The end of any statement is marked by a semicolon (;).
  • A semicolon is also used to separate multiple statements that appear on a single line.
  • SAS statements are not case sensitive and extra spacing before statements are automatically removed.
  • Comments can be included in the SAS program for statements in two different ways as:
    • A line beginning with an asterisk (*) and ending with a semicolon (;).
    • A line beginning with a forwarding slash and an asterisk (/*) and ending with an asterisk and a forward slash (*/).

Q #4) What are the data types that SAS contains?

Answer: ‘Numeric’ and ‘Character’ are the two types of data types which the SAS program contains.

Q #5) What are PDV and their functions?

Answer: Program Data Vector (PDV) is a logical concept and is defined as an area of memory where a data set is being built by SAS.

Functions of PDV are as follows:

  • A database having one observation at one time is created.
  • The input buffer for holding the data from an external file is created at the time of compilation.
  • PDV contains two automatic variables namely, _N_ (displays the count of the data step that is being executed) and _ERROR_ (notifies the error that occurs at the time of execution).

Q #6) What do you know about the SAS data set?

Answer: SAS data set is basically referred to as the data that is available for analysis within a SAS program. SAS dataset is also referred to as the SAS data table.

SAS data table consists of two parts:

  • Columns of variables
  • Rows of observations

Useful information about the SAS data set can be summarized as follows:

  • SAS Dataset can read as well as it has built-in data sources for use like Excel, Access, etc.
  • The dataset which is used only in the current session run and discarded after the session ends is known as Temporary Dataset.
  • The Dataset that is stored for use in the future session is also known as the Permanent Dataset.
  • The built-in data set can be accessed using this path Libraries -> My Libraries->SASHELP.

Q #7) Explain why double trailing @@ is used in Input Statements?

Answer: During data step iteration, including double trailing @@ in Input statements implies that SAS should hold the current record for the purpose of execution of the next Input statement rather than switching onto the new record.

Q #8) Explain the difference between NODUP and NODUPKEY options?

Answer: For removing duplicate values from the table, PROC SORT is basically categorized between two options:

  • NODUP
  • NODUPKEY

The difference between these two options can be seen below:

NODUPKEY NODUP
Compares just the BY variable present in the dataset. Compares all the variables present in the dataset.
Removes duplicate options for the values of variable listed in BY statement. Identifies and eliminates duplicate observations.
Syntax:
PROC SORT DATA=readin NODUPKEY;
BY variable name;
RUN;
Syntax:
PROC SORT DATA=readin NODUP;
BY variable name;
RUN;

Q #9) Which command is used to perform sorting in the SAS program?

Answer: PROC SORT command is used for performing sorting, be it on a single variable or multiple variables. This command is performed on the dataset where the new data set is created as a result of sorting but the original data set remains unchanged.

Syntax:

PROC SORT DATA=original OUT=Sorted;
BY variable;

Where,
‘Original’ refers to the original dataset
‘Sorted’ refers to the result as sorted dataset
‘Variable’ refers to the column on which sorting operation is done.

Sorting can be done in both ascending as well as descending order.

For the dataset to display in descending order, keyword ‘Descending’ is used in the BY statement with the column name on which sorting is to be performed.

PROC SORT DATA=original OUT=Sorted;
BY DESCENDING variable

Q #10) Explain the difference between Informat and Format with an example.

Answer: The difference between Informat and Format can be explained as:

Informat Format
Indicate SAS how to read data into SAS variable. Indicate SAS how to display values in the variable.
These are used to read the data or take input data from external files. These are used to write the data.

Q #11) Differentiate INPUT and INFILE.

Answer: Including an INFILE statement within the SAS programming identifies an external file that consists of the data, whereas including INPUT statement in SAS programming describes the variables used.

The syntax for INFILE:

INFILE ‘filename’;

The syntax for INPUT:

INPUT ‘varname1’ ‘varname2’;

Q #12) Explain the use of PROC print and PROC contents?

Answer: The PROC step of the SAS program is used to invoke built-in procedures for analyzing the data of the dataset.

PROC print: Ensures that the data present in the dataset are read correctly.

PROC contents: Displays the information about the SAS dataset.

Q #13) Explain DATA_NULL_?

Answer: As the name defines, DATA_NULL_ is a data step that actually does not create any data set.

It is used for:

  • Creating macro variables.
  • Writing the output without any data set.

Q #14) How is character variable converted into a numeric variable and vice versa?

Answer: Under SAS programming, there arise many tasks where a character value is to be converted into the numeric and in the same way, a numeric value is to be converted into a character value.

PUT() is used to convert numeric to character. In this case, the source format and source variable type must always be similar.

Example:

char_var= PUT( num_var, 6.);

INPUT() is used to convert a character to numeric. In this case, the source variable type must always be character variables.

Example:

Num_var= INPUT(char_var,2.0);

Q #15) What is the purpose of _CHARACTER_ and _NUMERIC_?

Answer: In the current dataset,

_CHARACTER_ defines all the character variables that are currently defined.

Example: To include all the character variables in PROC MEANS, the following statements are used:

PROC MEANS;
Var_character_;
Run;

_NUMERIC_ defines all the numeric variables that are currently defined.

Example: To include all the numeric variables in PROC MEANS, following statements are used:

PROC MEANS;
Var_numeric_;
Run;

Q #16) What commands are used in the case of including or excluding any specific variables in the data set?

Answer: DROP, KEEP, and data set options are used for this purpose.

The variable we want to remove from the data step is specified in the DROP statement.

The variable we want to retain from the data step is specified in the KEEP statement.

Q #17) Differentiate between PROC MEANS and PROC SUMMARY.

Answer: The difference between PROC MEANS and PROC SUMMARY can be understood as follows:

PROC MEANS PROC SUMMARY
This procedure produces the printed report by default in the OUTPUT window. This procedure includes the PRINT in the statement to produce the printed report.
PROC MEANS by default take all the numeric variables in the analysis. PROC SUMMARY takes the variables into the statistical analysis that are described in VAR statement.

Q #18) Explain the purpose of SUBSTR functions in SAS programming.

Answer: In SAS programming, whenever there is a requirement of the program to abstract a substring, the SUBSTR function is used in the case of a character variable.

When a start position and length are specified, then this function is used for abstracting character string.

Syntax: SUBSTR(char_var, start,length);

Q #19) Name and describe few SAS character functions that are used for data cleaning in brief.

Answer: Few SAS character functions that are used for data cleaning are enlisted below:

  • Compress(char_string) function is used for removing blanks or some specified characters from a given string.
  • TRIM(str) function is used for removing trailing blanks from a given string.
  • LOWCASE(char_string) function is used for converting all the characters in a given string to lowercase.
  • UPCASE(char_string) function is used for converting all the characters in a given string to uppercase.
  • COMPBL(str) function is used for converting multiple blanks to a single blank.

Q #20) Mention few ways with which a “table lookup’ is done in SAS programming.

Answer: In SAS programming, the table lookup values can be stored in the following ways:

  • Code
  • Array
  • Hash object
  • Format
  • Dataset

The following techniques are used to perform ‘table lookup’ in SAS respectively:

  • SELECT/WHEN or IF/THEN statements
  • Array Index value
  • Hash object key value
  • FORMAT statement, PUT function
  • Merge, join, KEY= Option

Let us see an example which shows the ‘Code’ way to perform table lookup by using ‘IF/THEN’ statements:

data location;
set myinfo;
if AreaCode='226' then Location='Ontario, Canada';
else if AreaCode='212' then Location='New York, NY';
else Location='Unknown';
run;

Q #21) Differentiate between CEIL and FlOOR functions.

Answer: CEIL  function is used for truncating numeric values where it displays the output as the smallest integer. By smallest integer, here means the integer value is greater than/equal to the argument.

Example: CEIL(12.85) will display output as 13.

FLOOR function is used for truncating numeric values where it displays the output as the greatest integer. By greatest integer, here means that the integer value is less than/equal to the argument.

Example: FLOOR(12.85) will display output as 12.

Q #22) What are the ways in which Macro variables can be created in SAS programming?

Answer: Well a number of different techniques can be used to create macro variables in SAS programming.

Enlisted below are the five most commonly used methods:

  • %LET statement
  • Macro parameters (named as well as positional)
  • %DO statement (iterative)
  • INTO in PROC SQL
  • CALL SYMPUTX routine

Q #23) Explain the purpose of the RETAIN statement.

Answer: As the meaning of the word ‘RETAIN’ signifies to keep the value once assigned, the purpose of RETAIN statement is the same in SAS programming as it’s meaning implies.

Within a SAS program, when it is required to move from the current iteration to the next of the data step, at that time RETAIN statement tells SAS to retain the values rather than set them to missing.

Example: Let us print a program that will display the output value of ‘z’ starting from 1 by using the RETAIN statement.

data abc;
set xyz;
RETAIN z 0;
z = z + 1;
run;

Q #24) Which command is used to save logs in the external file?

Answer: PROC PRINTTO command is used to save logs in the external file.

Example:

PROC PRINTTO log="C:\Users\abc\Downloads\LOG11.txt" new;
run;

Q #25) Mention some common errors that are usually committed in SAS programming.

Answer: Enlisted below are some of the common errors which are usually committed especially when you are new to this programming language.

  • The basic syntax includes a semicolon at the end of each statement and missing a semi-colon is the most common mistake.
  • You skip checking the logs after submitting the program.
  • Commenting errors like failing to use comments where necessary or using comments in an inappropriate way.
  • Not using proper debugging methods.

Q #26) Mention SAS system options to debug SAS macros.

Answer: To help in tracking the macro code as well as the SAS code generated by the macros, some system options can be used.

They are:

  • MLOGIC
  • MPRINT
  • SYMBOLGEN

The message that will be generated by these system options can be seen in the SAS log.

Q #27) Differentiate between SAS functions and SAS procedures.

Answer: The major differences can be discovered/understood by the case explained for both SAS functions and Procedures.

Case:

For Function, argument value is supplied or say taken for calculation across the observation mentioned in the program statement whereas, in the case of Procedure, every observation is expected to have only one variable through which calculation is done as mentioned in the below example.

Let us understand it with examples:

data average;
set temp;
avgtemp = mean( of T1 – T24 );
run;

Here in the above examples, the arguments passed to the mean function are taken for calculation as an observation.

proc sort;
by month;
run;

proc means;
by month;
var avgtemp;
run;

Here in the above example, Proc means function calculates the average temperature for one argument that is passed as an observation i.e. by month.

Q #28) What do you know about SYMPUT and SYMGET?

Answer: The major differences between the two are mentioned below.

SYMPUT is used for storing the value of a data set into the macro variable whereas SYMGET is used for retrieving the value from the macro variable to the data set.

Q #29) Explain the special input delimiters used in SAS programming.

Answer: The special input delimiters used in SAS programming are:

  • DLM
  • DSD

They are used in the statement ‘INFILE’ and DSD has the functionality of ignoring the delimiters that appear enclosed in quotation marks.

Q #30) Which function is used to count the number of intervals between two SAS dates?

Answer: Interval function INTCK is used for counting the number of intervals between two given SAS dates.

Syntax:

INTCK(interval,start-of-period,end-of-period)


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