This document provides an overview of SAS data sets and SAS programming. It discusses key concepts such as the two main parts of SAS programs (DATA and PROC steps), characteristics of SAS data sets such as variables and observations, and SAS libraries which are used to store SAS data sets. The document also provides examples of basic SAS code.
This document provides an overview of SAS (Statistical Analysis Software). It describes how SAS can handle large datasets with millions or billions of records. It also lists some common SAS modules and provides examples of DATA and PROC steps to create and process SAS datasets. Finally, it discusses the SAS programming environment and how to submit and run SAS programs.
This presentation is about -
Overview of SAS 9 Business Intelligence Platform,
SAS Data Integration,
Study Business Intelligence,
overview Business Intelligence Information Consumers ,navigating in SAS Data Integration Studio,
For more details Visit :-
http://vibranttechnologies.co.in/sas-classes-in-mumbai.html
This document provides an introduction and outline for using SAS software. It covers basic SAS windows and rules, loading and viewing data, manipulating data by selecting subsets, adding or deleting variables, sorting, summarizing data with procedures, and creating plots and outputting results to Word. Examples are provided for common procedures like SORT, MEANS, UNIVARIATE, FREQ, CORR and PLOT. Practice exercises are included to try these skills on a sample dataset.
This document provides instructions for inputting and managing data in SAS. It discusses creating a SAS library to organize data files. Steps are provided to manually create a SAS data set within a library and input data. Importing data from an external file is also mentioned as an alternative to manual input. The document reviews key SAS concepts like librefs and permanent vs temporary libraries.
SAS is a programming language that can be learned quickly. New users can write simple SAS programs within hours. SAS programs involve DATA and PROC steps - DATA steps input and process data, while PROC steps perform operations and output. The example SAS program reads student data from cards, assigns the values to variables in a DATA step, and prints the output in a PROC PRINT step. Additional PROC SORT and formatting options are demonstrated. The log file provides feedback on program execution and errors.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
Aan introduction to SAS, one of the more frequently used statistical packages in business. With hands-on exercises, explore SAS's many features and learn how to import and manage datasets and and run basic statistical analyses. This is an introductory workshop appropriate for those with little or no experience with SAS.
Complete workshop materials include demo SAS programs available at http://projects.iq.harvard.edu/rtc/sas-intro
This document provides an overview of the Statistical Analysis System (SAS) software. It discusses what SAS is used for, including data management, statistical analysis, reporting, and more. It also covers SAS components and their usage, how to install and use the SAS studio interface, basic SAS syntax like variables and data sets, and common statistical procedures in SAS like PROC MEANS, PROC FREQ, and PROC UNIVARIATE to produce measures, frequencies and graphs.
This document provides an overview of SAS (Statistical Analysis Software). It describes how SAS can handle large datasets with millions or billions of records. It also lists some common SAS modules and provides examples of DATA and PROC steps to create and process SAS datasets. Finally, it discusses the SAS programming environment and how to submit and run SAS programs.
This presentation is about -
Overview of SAS 9 Business Intelligence Platform,
SAS Data Integration,
Study Business Intelligence,
overview Business Intelligence Information Consumers ,navigating in SAS Data Integration Studio,
For more details Visit :-
http://vibranttechnologies.co.in/sas-classes-in-mumbai.html
This document provides an introduction and outline for using SAS software. It covers basic SAS windows and rules, loading and viewing data, manipulating data by selecting subsets, adding or deleting variables, sorting, summarizing data with procedures, and creating plots and outputting results to Word. Examples are provided for common procedures like SORT, MEANS, UNIVARIATE, FREQ, CORR and PLOT. Practice exercises are included to try these skills on a sample dataset.
This document provides instructions for inputting and managing data in SAS. It discusses creating a SAS library to organize data files. Steps are provided to manually create a SAS data set within a library and input data. Importing data from an external file is also mentioned as an alternative to manual input. The document reviews key SAS concepts like librefs and permanent vs temporary libraries.
SAS is a programming language that can be learned quickly. New users can write simple SAS programs within hours. SAS programs involve DATA and PROC steps - DATA steps input and process data, while PROC steps perform operations and output. The example SAS program reads student data from cards, assigns the values to variables in a DATA step, and prints the output in a PROC PRINT step. Additional PROC SORT and formatting options are demonstrated. The log file provides feedback on program execution and errors.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
Aan introduction to SAS, one of the more frequently used statistical packages in business. With hands-on exercises, explore SAS's many features and learn how to import and manage datasets and and run basic statistical analyses. This is an introductory workshop appropriate for those with little or no experience with SAS.
Complete workshop materials include demo SAS programs available at http://projects.iq.harvard.edu/rtc/sas-intro
This document provides an overview of the Statistical Analysis System (SAS) software. It discusses what SAS is used for, including data management, statistical analysis, reporting, and more. It also covers SAS components and their usage, how to install and use the SAS studio interface, basic SAS syntax like variables and data sets, and common statistical procedures in SAS like PROC MEANS, PROC FREQ, and PROC UNIVARIATE to produce measures, frequencies and graphs.
This document provides an introduction and overview of the SAS statistical software system. It discusses that SAS was originally developed in the 1970s for agricultural research, but is now widely used statistical software. It also summarizes the main SAS product lines, resources for learning SAS including introductory books and online documentation, and provides a basic overview of the SAS programming language including data steps, procedure steps, and accessing SAS.
The document provides an overview of SAS (Statistical Analysis System) software, including its applications, components, and tutorials. Key points include:
- SAS is an integrated suite of software used for data management, reporting, analytics, and more.
- It includes applications for executive information systems, data management, reporting, statistics, forecasting, and more.
- The document provides links to tutorials on base SAS, advanced SAS, macros, and certification preparation.
htttps://www.smartprogram.in/sas
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS
The document discusses SAS training which includes:
1) Reading data from raw data files, formatting the data, and performing statistical analysis and data manipulation.
2) Combining and subsetting different data sets.
3) Processing data iteratively through loops and producing final reports.
SAS is a software suite for advanced analytics. It was developed in the 1960s and includes components for statistical analysis, graphics, predictive modeling, and more. The main components of SAS are the data step for data manipulation and procedure steps for analysis. Common procedures include PROC PRINT, PROC MEANS, PROC FREQ and PROC REG. SAS programs are written in the SAS code editor and results are displayed in the SAS results window.
The concept about SAS software and it high end tools.
Stay connected for SAS programming Keywords.
Please not this uploaded ppt is not a copy right of any anonymous,this were created by Sushil Kasar for his basic learnings' and sharing Knowledge activities.
Regards,
Sushil & team.
This document provides a step-by-step guide to learning SAS. It begins with an introduction to SAS and its windowing environment. Next, it discusses SAS datasets and variables, including importing data into SAS and basic procedures and functions. The document then covers combining datasets in SAS before concluding with next steps. It assumes some basic database and analytics knowledge and provides disclaimers about its intended use as a high-level summary.
Introduction to Analytics
Introduction to SAS
Introduction to Satistics
Introduction to Predictive Modeling
Introduction to Forecasting
Introduction to Bigdata
This document provides an overview of using PROC SQL in SAS Enterprise Guide 4.3. It discusses the basics of SAS Enterprise Guide 4.3, the typical SQL statement structure including common clauses, best practices for order of operations and joins, and how to use macro variables with PROC SQL. The purpose is to provide guidance for both beginners and advanced users on effectively working with PROC SQL.
The document provides answers to common questions asked in SAS interviews or for SAS certification. Key points:
- The OUTPUT statement overrides automatic output in DATA steps and writes observations only when executed.
- The STOP statement stops processing the current DATA step and resumes after.
- DROP= in the SET statement drops variables from processing, while DROP= in the DATA statement drops them from the output dataset.
- The END= option reads the last observation of a dataset to a new dataset.
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS, Quick links, SAS Documentation, SAS Addin to Microsoft office, Oracle, ODS HTML, ODS< Clinical trials, Financial Industry, Q & A, SAS Resumes, SAS Blogs, http://sastechies.blogspot.com, http://www.sastechies.com
Sas Enterprise Guide A Revolutionary Toolsysseminar
The document describes SAS Enterprise Guide as a revolutionary tool that provides a point-and-click interface for SAS, allowing users to modify, analyze and report data without coding. It can increase efficiency, empower analysts without coding knowledge, and organize all SAS processes. The document highlights how SAS Enterprise Guide allows analysts to access and manipulate data, build queries, run analyses, and create reports and graphs through an intuitive graphical user interface without needing to learn SAS coding.
This document provides a summary of the SAS programming language and various SAS procedures. It describes the basic structure of a SAS job, SAS language elements like statements, comments, and variables. It also summarizes how to work with SAS data sets, the DATA and PROC steps for data manipulation and analysis, and some common statistical and graphical procedures.
This document provides an introduction and outline for a presentation on SAS (Statistical Analysis System). It discusses:
1. An overview of the SAS environment, including SAS programs, data sets, libraries, and the output windows.
2. Methods for working with and manipulating SAS data sets, including using SET, KEEP, DROP, and WHERE statements to select variables and observations from existing data sets.
3. Processing SAS data sets using procedures like SORT to arrange data and conditional logic with IF/THEN statements to subset observations.
This lesson covers creating and managing SAS datasets and formats. It teaches how to create permanent SAS datasets using the data statement, understand SAS libraries using the libname statement, modify SAS datasets, and create new variables using formats. Formats and labels are also discussed as ways to change how data values appear without changing the raw values. The key learning objectives are to create permanent SAS datasets, manage multiple SAS data sets and libraries, modify SAS datasets, understand the difference between formats and labels, and create new variables using formats.
This document provides an overview of writing a SAS program and importing data. It discusses utilizing SAS Studio to write a program, printing data from the program, and importing different data types like CSV and Excel files. The learning objectives are to write a SAS program, print data from the program, and import various data types. Sample code is provided to demonstrate writing a program that imports a soccer dataset and prints the player, age, and goals.
This lesson covers subsetting data, combining data sets through joins and merges, and utilizing SAS arrays. It introduces techniques for subsetting data using IF and WHERE statements in the data step and PROC statements. Methods for combining two or more datasets through one-to-one, one-to-many, inner, and excluding joins and the MERGE statement are explained. Finally, the use of SAS arrays to define and reference groups of variables is demonstrated through various examples.
Rational Publishing Engine and Rational System ArchitectGEBS Reporting
1. The document discusses how to publish documents from Rational System Architect using Rational Publishing Engine. It provides steps to obtain the SA schema, browse SA data, design an RPE template, and publish the final output document.
2. Key steps include adding REST data source schemas for Methods and Classes, configuring data sources, and using dynamic data sources to retrieve related Class details for each Method.
3. The template is designed to display Method details grouped under headings, along with associated Class name and attributes.
This document provides an overview and introduction to the SAS statistical software system. It discusses the origins and development of SAS, describes some of the main SAS products and their uses, and provides resources for further learning including introductory books and online materials. The document also outlines the basic structure of SAS programs including data steps, procedure steps, and accessing SAS on UNIX systems. It provides explanations of key concepts such as the structure of the data step and using the INPUT statement.
8323 Stats - Lesson 1 - 03 Introduction To Sas 2008untellectualism
This document provides an introduction to SAS, a statistical software used for business intelligence. It discusses the main programming windows in SAS including the editor, log, and output windows. It also describes how to access and manage SAS datasets by assigning libraries, and how SAS programs are made up of data and proc steps to import data, create and analyze SAS datasets, and produce outputs.
This document provides an introduction and overview of the SAS statistical software system. It discusses that SAS was originally developed in the 1970s for agricultural research, but is now widely used statistical software. It also summarizes the main SAS product lines, resources for learning SAS including introductory books and online documentation, and provides a basic overview of the SAS programming language including data steps, procedure steps, and accessing SAS.
The document provides an overview of SAS (Statistical Analysis System) software, including its applications, components, and tutorials. Key points include:
- SAS is an integrated suite of software used for data management, reporting, analytics, and more.
- It includes applications for executive information systems, data management, reporting, statistics, forecasting, and more.
- The document provides links to tutorials on base SAS, advanced SAS, macros, and certification preparation.
htttps://www.smartprogram.in/sas
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS
The document discusses SAS training which includes:
1) Reading data from raw data files, formatting the data, and performing statistical analysis and data manipulation.
2) Combining and subsetting different data sets.
3) Processing data iteratively through loops and producing final reports.
SAS is a software suite for advanced analytics. It was developed in the 1960s and includes components for statistical analysis, graphics, predictive modeling, and more. The main components of SAS are the data step for data manipulation and procedure steps for analysis. Common procedures include PROC PRINT, PROC MEANS, PROC FREQ and PROC REG. SAS programs are written in the SAS code editor and results are displayed in the SAS results window.
The concept about SAS software and it high end tools.
Stay connected for SAS programming Keywords.
Please not this uploaded ppt is not a copy right of any anonymous,this were created by Sushil Kasar for his basic learnings' and sharing Knowledge activities.
Regards,
Sushil & team.
This document provides a step-by-step guide to learning SAS. It begins with an introduction to SAS and its windowing environment. Next, it discusses SAS datasets and variables, including importing data into SAS and basic procedures and functions. The document then covers combining datasets in SAS before concluding with next steps. It assumes some basic database and analytics knowledge and provides disclaimers about its intended use as a high-level summary.
Introduction to Analytics
Introduction to SAS
Introduction to Satistics
Introduction to Predictive Modeling
Introduction to Forecasting
Introduction to Bigdata
This document provides an overview of using PROC SQL in SAS Enterprise Guide 4.3. It discusses the basics of SAS Enterprise Guide 4.3, the typical SQL statement structure including common clauses, best practices for order of operations and joins, and how to use macro variables with PROC SQL. The purpose is to provide guidance for both beginners and advanced users on effectively working with PROC SQL.
The document provides answers to common questions asked in SAS interviews or for SAS certification. Key points:
- The OUTPUT statement overrides automatic output in DATA steps and writes observations only when executed.
- The STOP statement stops processing the current DATA step and resumes after.
- DROP= in the SET statement drops variables from processing, while DROP= in the DATA statement drops them from the output dataset.
- The END= option reads the last observation of a dataset to a new dataset.
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS, Quick links, SAS Documentation, SAS Addin to Microsoft office, Oracle, ODS HTML, ODS< Clinical trials, Financial Industry, Q & A, SAS Resumes, SAS Blogs, http://sastechies.blogspot.com, http://www.sastechies.com
Sas Enterprise Guide A Revolutionary Toolsysseminar
The document describes SAS Enterprise Guide as a revolutionary tool that provides a point-and-click interface for SAS, allowing users to modify, analyze and report data without coding. It can increase efficiency, empower analysts without coding knowledge, and organize all SAS processes. The document highlights how SAS Enterprise Guide allows analysts to access and manipulate data, build queries, run analyses, and create reports and graphs through an intuitive graphical user interface without needing to learn SAS coding.
This document provides a summary of the SAS programming language and various SAS procedures. It describes the basic structure of a SAS job, SAS language elements like statements, comments, and variables. It also summarizes how to work with SAS data sets, the DATA and PROC steps for data manipulation and analysis, and some common statistical and graphical procedures.
This document provides an introduction and outline for a presentation on SAS (Statistical Analysis System). It discusses:
1. An overview of the SAS environment, including SAS programs, data sets, libraries, and the output windows.
2. Methods for working with and manipulating SAS data sets, including using SET, KEEP, DROP, and WHERE statements to select variables and observations from existing data sets.
3. Processing SAS data sets using procedures like SORT to arrange data and conditional logic with IF/THEN statements to subset observations.
This lesson covers creating and managing SAS datasets and formats. It teaches how to create permanent SAS datasets using the data statement, understand SAS libraries using the libname statement, modify SAS datasets, and create new variables using formats. Formats and labels are also discussed as ways to change how data values appear without changing the raw values. The key learning objectives are to create permanent SAS datasets, manage multiple SAS data sets and libraries, modify SAS datasets, understand the difference between formats and labels, and create new variables using formats.
This document provides an overview of writing a SAS program and importing data. It discusses utilizing SAS Studio to write a program, printing data from the program, and importing different data types like CSV and Excel files. The learning objectives are to write a SAS program, print data from the program, and import various data types. Sample code is provided to demonstrate writing a program that imports a soccer dataset and prints the player, age, and goals.
This lesson covers subsetting data, combining data sets through joins and merges, and utilizing SAS arrays. It introduces techniques for subsetting data using IF and WHERE statements in the data step and PROC statements. Methods for combining two or more datasets through one-to-one, one-to-many, inner, and excluding joins and the MERGE statement are explained. Finally, the use of SAS arrays to define and reference groups of variables is demonstrated through various examples.
Rational Publishing Engine and Rational System ArchitectGEBS Reporting
1. The document discusses how to publish documents from Rational System Architect using Rational Publishing Engine. It provides steps to obtain the SA schema, browse SA data, design an RPE template, and publish the final output document.
2. Key steps include adding REST data source schemas for Methods and Classes, configuring data sources, and using dynamic data sources to retrieve related Class details for each Method.
3. The template is designed to display Method details grouped under headings, along with associated Class name and attributes.
This document provides an overview and introduction to the SAS statistical software system. It discusses the origins and development of SAS, describes some of the main SAS products and their uses, and provides resources for further learning including introductory books and online materials. The document also outlines the basic structure of SAS programs including data steps, procedure steps, and accessing SAS on UNIX systems. It provides explanations of key concepts such as the structure of the data step and using the INPUT statement.
8323 Stats - Lesson 1 - 03 Introduction To Sas 2008untellectualism
This document provides an introduction to SAS, a statistical software used for business intelligence. It discusses the main programming windows in SAS including the editor, log, and output windows. It also describes how to access and manage SAS datasets by assigning libraries, and how SAS programs are made up of data and proc steps to import data, create and analyze SAS datasets, and produce outputs.
This document provides an introduction to SAS (Statistical Analysis System) including data management and analysis. It covers general topics such as the SAS interface, programs, data libraries and help/documentation. Specific techniques are explained like importing external data, combining and subsetting datasets, and commonly used functions. The document also gives examples of SAS statements for creating and analyzing datasets.
This document provides an introduction to SAS analytics training. It begins with introducing the instructor and their qualifications. It then outlines what will be covered in the training, including an introduction to analytics, the top 5 features of SAS, different types of SAS datasets, how to read data into SAS, and how to plot graphs to understand data. It also discusses what SAS is and why it is widely used, highlighting its maturity, certification programs, product support, and role in large enterprises.
This document discusses SAS data libraries and how to explore them using PROC CONTENTS. Key points include:
1) SAS data libraries allow you to assign nicknames (librefs) to file paths to reference SAS data sets more efficiently.
2) By default, SAS provides a temporary WORK library and a permanent SASUSER library when a session starts.
3) The LIBNAME statement assigns a libref to a file path, making that library available for referencing data sets.
4) PROC CONTENTS lists information about SAS data sets within a library. The NODS option lists only file names without descriptor details.
I need help with Applied Statistics and the SAS Programming Language.pdfMadansilks
I need help with Applied Statistics and the SAS Programming Language
Solution
Introduction :
All SAS jobs are a sequence of SAS steps, which are
made up of instructions, which are called SAS
statements. There are only two kinds of SAS steps:
DATA steps are used to read, edit, and transform data
(raw data or SAS data files), to prepare SAS data sets,
PROC steps are ready-to-use procedures which
analyze or process SAS data sets. In general, data
must be in a SAS data file before they can be
processed by SAS procedures.
Without going into the details at this time, here is a
skeletal example of a SAS job:
DATA STUDENTS;
INPUT NAME $ 1-14 SEX $ 15
SECTION $ 17-19 GRADE;
DATALINES;
. . . data lines . . .
;
PROC SORT DATA=STUDENTS;
BY SECTION DESCENDING GRADE;
PROC PRINT DATA=STUDENTS;
BY SECTION;
RUN
There are two kinds of SAS data sets: SAS data files (or tables), and SAS data views. A SAS
data file contains: the descriptor portion, which provides SAS procedures and some DATA step
statements with descriptive information (data set attributes and variable attributes) about the data
, and the data portion, a rectangular structure containing the data values, with rows (customarily
called observations), and columns (customarily called variables); and which is passed to most
procedures, observation by observation. A SAS catalog is a type of SAS file which stores many
different types of information used by the SAS System. All SAS files reside in a SAS data
library. The SAS System processes the program in two steps: (1) it compiles the program, and
(2) it executes the program. When the program is compiled, a program data vector (PDV) is
constructed for each DATA step. It is an area of memory which includes all variables which are
referenced either explicitly or implicitly in the DATA step. At execution time, the PDV is the
location where the current working values are stored as they are processed by the DATA step.
Variables are added to the PDV sequentially as they are encountered during parsing and
interpretation of SAS source statements. Each step (DATA or PROC) is compiled and executed
separately, in sequence. And at execution time within each DATA step, each observation is
processed iteratively through all of the SAS programming statements of the DATA step. SAS
procedures (PROCs) are programs that are designed to perform specific data processing and
analysis tasks on SAS data sets. Base/SAS procedures fall into the following categories: SAS
Utilities -- APPEND, CATALOG, CIMPORT, COMPARE, CONTENTS, COPY, CPORT,
DATASETS, DBCSTAB, DISPLAY, EXPLODE, EXPORT, FORMAT, FSLIST, IMPORT,
OPTIONS, PMENU, PRINTTO, RANK, REGISTRY, SORT, SQL, STANDARD,
TRANSPOSE, TRANTAB; Descriptive Statistics -- CORR, FREQ, MEANS, SQL,
SUMMARY, TABULATE, UNIVARIATE; Reporting -- CALENDAR, CHART, FORMS,
MEANS, PLOT, PRINT, REPORT, SQL, SUMMARY, TABULATE, TIMEPLOT.
Creating SAS Data Files Since SAS procedures can operate only on SAS data sets, then the first
step in processing any .
This document provides an introduction and overview of SAS programming, including descriptions of SAS datasets, variables, syntax, windows, and common procedures. It discusses the structure of SAS datasets which have a descriptor section and data section, and describes attributes of variables like name, type, and format. It also summarizes SAS syntax rules, comments, libraries, and how to use procedures like REG and UNIVARIATE.
This document provides an overview of using SPSS (Statistical Package for the Social Sciences) software. It discusses installing sample data files, introduces the main interface windows including the data view, variable view and output view. It also covers how to define variable types, enter and modify data, perform basic analyses like frequencies and cross tabulations, and create charts from the output. The document is intended to help new users learn the basics of navigating the SPSS program and conducting initial analyses.
The document provides an introduction to the SAS programming environment and basic SAS syntax. It describes the five main windows in SAS - Explorer, Editor, Log, Output, and Results. It outlines some basic SAS syntax rules, including using semicolons to end commands and asterisks to denote comments. It also describes steps for running a SAS program, including opening a sample SAS file, running the code, and checking the log for errors or output. The document provides examples of DATA and PROC steps to work with sample data.
SPSS is a statistical software package used for data management and analysis. It can import data from various file formats, perform complex statistical analyses and generate reports, tables, and graphs. Some key features include an easy to use interface, robust statistical procedures, and the ability to work with different operating systems. While powerful and popular, SPSS is also expensive and less flexible than open-source alternatives like R for advanced or custom analyses.
This document provides an overview of basic SAS commands for inputting and analyzing data. It describes the SAS data step for inputting and manipulating data to create SAS datasets. It then summarizes commonly used SAS statistical procedures like ANOVA, CHART, CORR, and REG for analyzing SAS dataset. It includes syntax examples and explanations of options for these procedures.
The document discusses the SAS windowing environment and how to use it for programming and working with datasets. Key features of the SAS window include the program editor, log and output windows, and explorer window for navigating libraries and files. Basic operations involve writing programs in the editor, submitting them to run, and examining the results. Examples show how to create and manage datasets by writing DATA steps, and printing output.
This presentation is about -
Working Under Change Management,
What is change management? ,
repository types using change management
For more details Visit :-
http://vibranttechnologies.co.in/sas-classes-in-mumbai.html
This document provides an overview and summary of the key features of the statistical software package SPSS (Statistical Package for the Social Sciences). It describes how SPSS can be used to perform statistical analysis and data management. The summary includes descriptions of the data editor, viewer, pivot tables, database access, transformations, and other core features. Procedures in SPSS can be accomplished through dialog boxes and menus using point and click functionality.
This document summarizes the key information about installing and using SPSS 11.5 for Windows. It outlines the operating system requirements, installation process, new features in 11.5 including new data definition tools and two-step cluster analysis, and known issues such as limitations of using files saved in SAS formats in other applications and performance issues with large datasets. The document provides guidance on installation, configuration, use, and troubleshooting of SPSS 11.5 for Windows.
This document provides an overview of how to use SPSS to enter and modify data. It discusses defining variable types like numeric, string, date in the variable view. It also covers creating a new dataset, recoding variables to group data into categories, and using the recoding tool to transform continuous variables into categorical variables for analysis. The document demonstrates how to backup original data before recoding and reintroduces the exceptions for recoding special variable types.
This document provides an overview of using SPSS (Statistical Package for the Social Sciences) software. It introduces the main interfaces for working with data in SPSS, including the data view, variable view, output view, draft view, and syntax view. It also provides instructions for installing sample data files and demonstrates how to generate a basic cross-tabulation output of employment by gender using the automated features.
This document provides an introduction to using SPSS (Statistical Package for the Social Sciences) software. It covers opening and navigating SPSS, cleaning and transforming data, descriptive statistics, graphs and charts, and saving work. The topics are demonstrated using a sample education data set. Key functions covered include selecting cases, recoding variables, descriptive statistics like frequencies and crosstabs, formatting histograms and other graphs, and performing a one-way ANOVA test. Resources for further learning SPSS are also provided.
Top 140+ Advanced SAS Interview Questions and Answers.pdfDatacademy.ai
SAS Interview Questions and Answers is a guide for individuals preparing for a job interview in the field of SAS (Statistical Analysis System). The guide includes a range of commonly asked interview questions and their answers, covering topics such as SAS programming, data manipulation, analytics, and more. It aims to help candidates prepare for the interview and showcase their knowledge and expertise in SAS.
Visit by :- https://www.datacademy.ai/sas-interview-questions-answers/
#SASInterview #SASInterviewQuestions #SASInterviewPrep #SASProgramming #DataAnalytics #DataManipulation #SASJobs #SASCareer #SASSkills #DataScience #InterviewPreparation
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
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1. Introduction
To program effectively using SAS, you need to understand basic concepts about SAS
programs and the SAS files that they process. In particular, you need to be familiar
with SAS data sets.
In this lesson, you'll examine a simple SAS program and see how it works. You'll learn
details about SAS data sets (which are files that contain data that is logically arranged
in a form that SAS can understand). Finally, you'll see how SAS data sets are stored
temporarily or permanently in SAS libraries.
Editor
This window is a text editor. You can use it to type in, edit, and submit SAS programs as
well as edit other text files such as raw data files. In Windows operating environments,
the default editor is the Enhanced Editor. The Enhanced Editor is syntax sensitive and
color codes your programs making it easier to read and find mistakes. The Enhanced
Editor also allows you to collapse and expand the various steps in your program. For
other operating environments, the default editor is the Program Editor whose features
vary with the version of SAS and operating environment.
2. Log
The Log window contains notes about your SAS session, and after you submit a SAS
program, any notes, errors, or warnings associated with your program as well as the
program statements themselves will appear in the Log window.
Output
If your program generates any printable results, then they will appear in the Output
window.
Results
The Results window is like a table of contents for your Output window; the results tree
lists each part of your results in an outline form.
Explorer
The Explorer window gives you easy access to your SAS files and libraries.
SAS Programs
Layout of SAS programs
There really aren’t any rules about how to format your SAS program.
While it is helpful to have a neat looking program with each statement on a line by
itself and indentions to show the various parts of the program, it isn’t necessary.
1. SAS statements can be in upper- or lowercase.
2. Statements can continue on the next line (as long as you don’t split words in two).
3. Statements can be on the same line as other statements.
4. Statements can start in any column.
The Two Parts of a SAS Program
3. DATA steps PROC steps
1. Begin with DATA statements 1. Begin with PROC statements
2. Read and modify data 2. Perform specific analysis or function
3. Create a SAS data set 3. Produce results or report
Sample program
Data work.clinic;
Input Name$ Age Gender$;
Cards;
Shilpa 23 female
Ravi 24 male
Pradip 24 male
Sweta 23 female
Run;
Characteristics of SAS Programs
Next let's look at the individual statements in our sample program. SAS programs consist
of SAS statements. A SAS statement has two important characteristics:
• It usually begins with a SAS keyword.
• It always ends with a semicolon.
Statements Sample Program Code
a DATA statement DATA work.clinic;
a INPUT statement Input Name$ Age Gender$;
a CARDS statement Cards;
a RUN Statement Run;
Issue the SUBMIT command or click on Submit or select Run _ Submit to submit the
program for execution.
4. Data types
Raw data come in many different forms, but SAS simplifies this. In SAS there are just
two data types: numeric and character. Numeric fields are, well, numbers. They can be
added and subtracted, can have any number of decimal places, and can be positive or
negative. In addition to numerals, numeric fields can contain plus signs (+), minus signs
(-), decimal points (.), or E for scientific notation. Character data are everything else.
They may contain numerals, letters, or special characters (such as $ or !) and can be up to
32,767 characters long.
Rules for SAS names
You make up names for the variables in your data and for the data sets themselves. It is
helpful to make up names that identify what the data represent, especially for variables.
While the variable names A, B, and C might seem like perfectly fine, easy-to-type names
when you write your program, the names Sex, Height, and Weight will probably be more
helpful when you go back to look at the program six months later. Follow these simple
rules when making up names for variables and data set members:
1. Names must be 32 characters or fewer in length.3
2. Names must start with a letter or an underscore (_).
3. Names can contain only letters, numerals, or underscores (_). No %$!*&#@,
please.4
4. Names can contain upper- and lowercase letters.
Reading the SAS Log
Every time you run a SAS job, SAS writes messages in your log. Many SAS
programmers ignore the SAS log and go straight to the output. That’s understandable, but
dangerous. It is possible and sooner or later it happens to all of us to get bogus results that
look fine in the output. The only way to know they are bad is to check the SAS log. Just
because it runs doesn’t mean its right.
1 DATA work.clinic;
2 Input Name$ Age Gender$;
3 Cards;
NOTE: The data set WORK.CLINIC has 4 observations and 3 variables.
NOTE: DATA statement used (Total process time):
real time 0.31 seconds
cpu time 0.00 seconds
8 Run;
5. SAS Data Sets
Overview of SAS Data Sets
As you saw in our sample program, for many of the data processing tasks that you
perform with SAS, you
• Access data in the form of a SAS data set
• Analyze, manage, or present the data.
Conceptually, a SAS data set is a file that consists of two parts: a descriptor portion and
a data portion. Sometimes a SAS data set also points to one or more indexes, which
enable SAS to locate records in the data set more efficiently. (The data sets that you work
with in this lesson do not contain indexes.)
Length
A variable's length (the number of bytes used to store it) is related to its type.
• Character variables can be up to 32K long.
• All numeric variables have a default length of 8. Numeric values (no matter how
many digits they contain) are stored as floating-point numbers in 8 bytes of
storage, unless you specify a different length.
6. Missing data
Sometimes despite your best efforts, your data may be incomplete. The value of a
particular variable may be missing for some observations. In those cases, missing
character data are represented by blanks, and missing numeric data are represented by a
single period (.).
Size of SAS data sets
Prior to SAS 9.1, SAS data sets could contain up to 32,767 variables.
Beginning with SAS 9.1, the maximum number of variables in a SAS data set is limited
by the resources available on your computer but SAS data sets with more than 32,767
variables cannot be used with earlier versions of SAS. The number of observations, no
matter which version of SAS you are using, is limited only by your computer’s capacity
to handle and store them.
SAS Libraries
Sashelp
A permanent library, that contains sample data and other files which control how SAS
works at your site. This is a read-only library.
Sasuser
7. A permanent library that contains SAS files in the Profile catalogs that store your
personal settings. This is also a convenient place to store your own files.
Work
A temporary library for files that do not need to be saved from session to session.
Creating a new library
You can create new SAS libraries using the New Library window. To open this window,
either left click in the Active Libraries window (to make it active) and choose New from
the File menu, or right click in the Active Libraries window and choose New from the
pop-up menu.
8. In the New Library window, type the name of the library you want to create. This name is
called a libref which is short for library reference. A libref must be eight characters or
fewer; start with a letter or underscore; and contain only letters, numerals, or underscores.
In this window, the name Mylib has been typed in as the libref. In the Path field, enter the
complete path to the folder or directory where you want your data sets to be stored, or
choose the Browse… button to navigate to the location. If you don’t want to define your
library reference every time you start up SAS, then check the Enable at startup box. Click
OK and then your new library reference will appear in the Active Libraries window. Here
is the Active Libraries window showing the newly created Mylib library.
OR
Libname Mylib ‘D: ’; - in Editor Window.
Deleting Data sets
Proc datasets library = SAS library name;
Delete SAS-dataset list;
Run;
Properties of Data sets
9. PROC CONTENTS DATA = SAS-file-specification NODS;
RUN;
SAS-file-specification specifies an entire library or a specific SAS data set within a
library. SAS-file-specification can take one of the following forms:
o <libref.>SAS-data-set names one SAS data set to process.
o <libref.>_ALL_ requests a listing of all files in the library. (Use a
period (.) to append _ALL_ to the libref.)
• NODS suppresses the printing of detailed information about each file when you
specify _ALL_. (You can specify NODS only when you specify _ALL_.)
Selected Menus (as displayed in the Windows operating environment)
Select items from this menu ... To ...
10. open main SAS windows.
From the Explorer window, you can
use this menu to show or hide details
and a tree view.
submit and recall SAS programming
statements in the Program Editor
window.
access ready-to-use solutions and
applications.
11. get more help.
SAS System Options
If you create your procedure output as a SAS listing, you can also control the appearance
of your output by setting system options such as
• line size (the maximum width of the log and output)
• page size (the number of lines per printed page of output)
• The display of page numbers.
• The display of date and time.
Not all options are available for all operating environments. A list of options specific to
your operating environment appears in the SAS Help and Documentation. You can see a
list of system options and their current values by opening the SAS System Options
window or by using the OPTIONS procedure. To use the OPTIONS procedure, submit
the following SAS program and view the results in the SAS log:
PROC OPTIONS;
RUN;
12. Common options
The following are some common system options you might want to use:
CENTER | NOCENTER Controls whether output are centered or left-justified.
Default: CENTER.
DATE | NODATE Controls whether or not today’s date will appear at the
top of each page of output.
Default: DATE.
LINESIZE = n Controls the maximum length of output lines.
Possible values for n are 64 to 256. Default varies.
NUMBER | NONUMBER Controls whether or not page numbers appear on each
page of SAS output. Default: NUMBER.
ORIENTATION = PORTRAIT Specifies the orientation for printing output.
ORIENTATION = LANDSCAPE Default: PORTRAIT
PAGENO = n Starts numbering output pages with n. Default is 1.
PAGESIZE = n Controls the maximum number of lines per page of
output. Possible values for n are 15 to 32767.
Default varies.
RIGHTMARGIN = n Specifies size of margin (such as 0.75in or 2cm) to be
LEFTMARGIN = n printing output. Default: 0.00in.
TOPMARGIN = n
BOTTOMMARGIN = n
13. Extraction of Data
Extraction from notepad
Create notepad file with the name of sales and put following data…
For extraction of data from notepad write program in Editor Window of SAS.
Create file in notepad with following data with name of
Sales
Chocolate 213 123
Vanilla 213 512
Chocolate 415 242
Write following program in SAS Editor Window.
DATA icecream;
INFILE ’c:MyRawDataSales.txt’;
INPUT Flavor $ 1-9 Location BoxesSold;
RUN;
Extraction from Excel
Using the Import Wizard1, you can read a variety of data file types into SAS by simply
answering a few questions. The Import Wizard will scan your file to determine variable
types2 and will, by default, use the first row of data for the variable names. Start the
Import Wizard by choosing Import Data… from the File menu. Select the type of file you
are importing by choosing from the list of standard data sources such as Excel 97, excel
2000, etc...
OR
Proc import file = ‘path of excel file’ out = sas-data set name;
Run;
14.
15.
16. SET – copying datasets
The SET statement is flexible and has a variety of uses in SAS programming. These uses
are determined by the options and statements that you use with the SET statement. They
include
• reading observations and variables from existing SAS data sets for further
processing in the DATA step
• concatenating and interleaving data sets, and performing one-to-one reading of
data sets
• Reading SAS data sets by using direct access methods.
Data test;
Set Sashelp.Air;
Run;
FIRSTOBS= The FIRSTOBS= option tells SAS at what line to begin reading data.
Data test;
Set Sashelp.air (firstobs = 10);
Run;
OBS= The OBS= option can be used anytime you want to read only a part of your data
file. It tells SAS to stop reading when it gets to that line in the raw data file.
Data test;
Set Sashelp.air (obs = 10);
Run;
Data test;
Set sashelp.class(firstobs =5 obs = 10);
Run;
In above example, work.test having 6 observations.