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SAS - Base and Advance Training

LIVE
3 reviews
60 Hours

Course offered by Complete Analytics

24 reviews

This SAS training class covers SAS Base and Advanced Modules. • SAS/BASE • SAS/SQL • SAS/MACROS • SAS/GRAPHS • SAS/STAT • SAS/ACCESS • SAS/ODS

Topics Covered

1. Introduction • How to Use this Document • Little Bit History About SAS • What is SAS? • Launching SAS • Windows in SAS for Windows • Menus in SAS • Working within SAS • Using the Cursor • Using Icons • Using the Enhanced Editor • Writing a SAS Program: the DATA Step 2. Introduction to SAS Programming • Introduction to SAS® • SAS® Software Versions • Using SAS for Windows • System Requirement • Installing SAS® 9.1.3 for MS.Windows,Unix,Linux,Vms,Open/390 3. Accessing Data • Introduction • LIST,COLUMN,FORMTTED AND NAMED input to read raw data • Using Various Components of an INPUT Statement • Importing raw data from Excel files, Text files, CSV files, ODBC and Access files Etc... using the import procedure, data step and Import wizard • Set statement to read and combine SAS data sets • Using the merge statement to combine SAS data sets • Appending multiple SAS data sets • Explaining about User created functions and system defined functions • Explaining about Types of functions such as Character, Numeric, statistical or mathematical and date or time functions • Statements and types, global statements and local statements • Using loops for easy manipulations • SQL procedure to create data sets • SQL procedure to query multiple tables 4. Creating Data Structures • Introduction • Creating temporary and permanent SAS data sets • Preparing temporary libraries and permanents libraries • Applying conditional assignments and conditional subsets • Using data step statements to export(or write) data to a file • Exporting data to excel and access using the export procedure • Understanding how the data step is compiled and executed • Using data dynamic exchange(DDE) to import excel data • Exporting SAS files to Excel Using DDE. 5. Managing Data • Introduction • Modifying variable attributes in the data set • Assignment statement to accumulate variable values across executions of the data step • Using SAS functions to manipulate character data, numeric data, and SAS date and time values • Creating User defined in formats and Formats • Changing SAS default setting using system options, data step options and statement options • Use system defined and user defined formats • Use system defined and user defined in formats • Use SAS functions to convert character data to numeric data and vice versa • Processing data using SAS arrays • Sorting observations in a SAS data set • Using SAS utility procedure to investigate SAS data libraries 6. Generating Reports • Introduction • Generating reports using the PRINT,MEANS,FREQ,TABULATE,REPORT etc…procedures • Generating HTML, RTF, PDF, EXCEL, TEXT, CSV, and PDF reports using ODS statements • Enhancing reports with options and statements 7. Handling Errors • Introduction… • Recognizing and correcting syntax and non-syntax errors • Examining and resolving data errors • Program debugging techniques SAS Statistics 8. Descriptive Statistics • Introduction statistics • Overview • Data Presentation • Data Characteristics: Descriptive Summary Statistics • Probability: Basic Concepts • Basic Probability Distribution • Sampling & Estimation 9. Categorical data Analysis • Introductions • Procedures • Cross tabulations • Frequencies from one way frequencies to N way frequencies 10. Hypothesis Testing • T-Test : Testing differences between two means • Random assignment of subjects • Two independent samples : Distribution free tests • One-tailed vs. two tailed tests • Paired t-tests(related samples) 11. Hypothesis Testing (More than two groups) • One-way analysis of variance • Analysis of variance : two independent variables • Interpreting significant interactions • N-way factorial designs • Unbalanced designs: Proc GLM 12. Regression Analysis • Introduction • Simple regression and multiple regression analysis • Logistic regression • Non-experimental regression • Interpretation about statistics such as (R square, adjusted R square, etc…..) 13. Correlation Analysis • Introduction • Positive correlation and negative correlation • Multiple correlation and partial correlation • Linear and non-linear correlation SAS Macros • Introduction • Creating macro variables • Reusing macro variable • Working with system defined macro variables and user defined macro variables • Converting Global macro variables into local macro variables vice versa • Functions and routines, its different • Introduction to Macro Processing • Defining and Calling Macros • How the Macro Processor Compiles a Macro Definition • How the Macro Processor Executes a Compiled Macro • Summary of Macro Processing • System defined macro options • Creating macro and Reusing macro • Executing a macro program • Passing values to a macro program through macro parameters • Using SAS Base functions and Proc SQL statements in SAS macros • Using conditional statements in macros • Manipulating SAS Base programs to macros • Macro quoting functions • Macro facility error messages and debugging • Using the stored compiled macro facility for saving macro • Arithmetic and logical expressions • Reading external files using macros • Writing SAS files using macros • Stepwise method for writing macro programs • Saving Macros in an Auto call Library • Saving Macros Using the Stored Compiled Macro Facility SAS SQL • Introduction to the SQL Procedure • What Is SQL? • What Is the SQL Procedure? • Comparing PROC SQL with the SAS DATA Step • Creating data sets using SQL procedure • Overview of the query window • Retrieving Data from a Single Table • Retrieving Data from Multiple Tables • Creating and Updating Tables and Views • Inserting Rows into Tables • Updating Data Values in a Table • Deleting Rows and Tables • Altering Columns • Creating an Index • Using SQL Procedure Tables in SAS Software • Creating and Using Integrity Constraints in a Table • Using PROC SQL Options to Create and Debug Queries • Improving Query PerformanceHYPERLINK "a001385596.htm"Accessing SAS System Information Using DICTIONARY Tables • Using the Output Delivery System (ODS) with PROC SQL • Performing simple queries • Combine tables using inner join, outer join(outer left join, outer right join, outer full join) • Summarizing groups of data • Sub setting groups of data • Handling missing values • Handling embedded blanks in column names • Using SAS base functions in SQL • Building calculated columns • Reading oracle data tables into SAS by pass through facility • Connecting to Oracle, DB2, SYBASE, EXCEL, ACCESS, ODBC, OSIRIS, REMOTE, SPDE, SPSS, TERADATA, XML, AND XPORT engines etc…. to import data sets • Explaining about conditional statements • Modifying variables using Base Options in SQL • Creating macro variables in SQL SAS Graphs • Introduction • Drawing graphs by programming and menu driven • Using colors and images • Language Elements • SAS Data Sets • Using Engines with SAS/GRAPH Software • Running SAS/GRAPH Programs • Procedure Output and the Graphics Output Area • Printing Graphics Output • Storing Graphics Output in SAS Catalogs • Modifying SAS/GRAPH Output • Transporting and Converting Graphics Output • Using SAS/GRAPH Colors and Images • Specifying Colors in SAS/GRAPH Programs • Specifying Images in SAS/GRAPH Programs • GChart • GPlot • Vbar • Hbar • Block bar • Star chart • Pie chart • Histogram • Box plot • Probability plot • Scatter plot (two dimensional and three dimensional) • Surface plot SAS ODS • Creating HTML outputs Using ODS • Creating HTML outputs with a Table of Contents • Selecting ODS tables for Display • Excluding ODS tables for Display • Exporting SAS outputs • Preparing PDF,RTF,CSV,XML,HTML files using ODS • Creating an output data set from an ODS tables • Generating outputs in colors • Creating an output data set from sub setting the data • Determining the Names of ODS Tables • Using the TEMPLATE Procedure to Customize Output • Creating HTML Output, Linked Within a Single Analysis • Creating HTML Output, Linked Between Analyses

Who should attend

Any graduate/MBA/Post Graduates

Pre-requisites

No pre-requisites

What you need to bring

Nothing

Key Takeaways

SAS Programming. Data preparation using SAS, Statistical Analysis using SAS and Reporting in SAS

Gallery (4)

About the Trainer

4.9 Avg Rating

24 Reviews

19 Students

12 Courses

Complete Analytics

M.Sc. Statistics Certified Advance Programmer for SAS 9 Certified Predictive Modeler using SAS Enterprise Miner 6 SAS Certified Data Integration Developer for SAS 9 Certified BI Content Developer for SAS 9

Previous work experience
Worked as Business Analyst, SAS Mentor and Lead Statistician in various domains.
Build supervised/unsupervised models (Linear Regression, Logistic regression, Decision Tree, MBA, Clustering, RFM, PCA, SVM, NB, RF, NLP (Sentiment Analysis, network analysis), and Neural Network) by using various SAS products and using other Statistical packages like SPSS modeler /Python/Pyspark
Perform data quality check and create different matrices in all Research and Analytics projects.
Well versed with email campaign reporting (like open rate, click to open rate and optout rates based on different segments)
Provide training in SAS, SPSS Modeler, SAS E-MINER, SAS CI Studio, SAS MA, SAS DM and SAS Management Console to other associates
Migrating SAS codes to R

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4 out of 5 3 reviews

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"I Joined Complete Analytics, For Predictive Modeling course. Course instructor is very knowledgeable. He describes you course in detail. All Presentations are very good.I personally Recommend this institute is good for Analytics. "

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SAS - Base and Advance Training

"Complete Analytics is a well experienced institute. I have taken the SAS course, the course was excellent. It is the best center for SAS course. Trainer is very knowledgeable and friendly with the students. I wish to thanks to my teacher as well as institute. "

Complete Analytics
S

SAS - Base and Advance Training

"Complete Analytic is a well experienced training institute. Good personal attention I got trained on SAS course Course is exhaustive. What I like the most is the personal attention given to each student based on one's grasping & understanding capabilities. "

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4 out of 5 3 reviews

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4.5053
Complete Analytics
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Python for DataScience

"I Joined Complete Analytics, For Predictive Modeling course. Course instructor is very knowledgeable. He describes you course in detail. All Presentations are very good.I personally Recommend this institute is good for Analytics. "

Complete Analytics
P

SAS - Base and Advance Training

"Complete Analytics is a well experienced institute. I have taken the SAS course, the course was excellent. It is the best center for SAS course. Trainer is very knowledgeable and friendly with the students. I wish to thanks to my teacher as well as institute. "

Complete Analytics
S

SAS - Base and Advance Training

"Complete Analytic is a well experienced training institute. Good personal attention I got trained on SAS course Course is exhaustive. What I like the most is the personal attention given to each student based on one's grasping & understanding capabilities. "

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